From ca37bfd0175b632aae7539cb6d91b9c2ddcc198f Mon Sep 17 00:00:00 2001 From: AntonJMLarsson Date: Mon, 7 Jan 2019 15:02:07 +0100 Subject: [PATCH] Uploaded figure notebooks --- ExtDataFig1i.ipynb | 129 ++++ ExtFig1b.ipynb | 413 +++++++++++ Fig 1b.ipynb | 540 +++++++++++++++ Figure 1a.ipynb | 252 +++++++ Figure 1c-d, 1g and ExtDataFig 3f.ipynb | 215 ++++++ Figure 1e, 1f.ipynb | 143 ++++ Figure 2b-c, ExtDataFig 3a-e, g.ipynb | 887 ++++++++++++++++++++++++ Figure 3a-d, ExtDataFig 5a-f.ipynb | 662 ++++++++++++++++++ Figure 3e, ExtDataFig 7a-f.ipynb | 382 ++++++++++ Figure 4a-c, ExtDataFig 8a-d, 5g.ipynb | 457 ++++++++++++ 10 files changed, 4080 insertions(+) create mode 100644 ExtDataFig1i.ipynb create mode 100644 ExtFig1b.ipynb create mode 100644 Fig 1b.ipynb create mode 100644 Figure 1a.ipynb create mode 100644 Figure 1c-d, 1g and ExtDataFig 3f.ipynb create mode 100644 Figure 1e, 1f.ipynb create mode 100644 Figure 2b-c, ExtDataFig 3a-e, g.ipynb create mode 100644 Figure 3a-d, ExtDataFig 5a-f.ipynb create mode 100644 Figure 3e, ExtDataFig 7a-f.ipynb create mode 100644 Figure 4a-c, ExtDataFig 8a-d, 5g.ipynb diff --git a/ExtDataFig1i.ipynb b/ExtDataFig1i.ipynb new file mode 100644 index 0000000..840d116 --- /dev/null +++ b/ExtDataFig1i.ipynb @@ -0,0 +1,129 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "c57_UMI = pd.read_csv('data/SS3_c57_UMIs_concat.csv', index_col=0)\n", + "cast_UMI = pd.read_csv('data/SS3_cast_UMIs_concat.csv', index_col=0)\n", + "c57_UMI = c57_UMI.dropna(how='all')\n", + "cast_UMI = cast_UMI.dropna(how='all')\n", + "c57_UMI = c57_UMI.fillna(0)\n", + "cast_UMI = cast_UMI.fillna(0)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "silent = (c57_UMI == 0)&(cast_UMI == 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "biallelic = (c57_UMI > 0)&(cast_UMI > 0)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "10727" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(silent)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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gV5s3QL5dc1R39mqCQ6BFJv3ow6akYw85PcR93Zjiv4jT5SMQjjEQjBj36AtE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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(100*silent.mean(axis=1), 100*biallelic.mean(axis=1), s=1)\n", + "plt.xlabel('Silent cells (%)')\n", + "plt.ylabel('Biallelic cells (%)')\n", + "plt.savefig('figures/ExtDataFig1i.pdf')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/ExtFig1b.ipynb b/ExtFig1b.ipynb new file mode 100644 index 0000000..2bd3bc2 --- /dev/null +++ b/ExtFig1b.ipynb @@ -0,0 +1,413 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from scipy.interpolate import interp1d\n", + "from scipy.optimize import minimize\n", + "from scipy import special\n", + "from scipy.stats import poisson,norm\n", + "from scipy.special import j_roots\n", + "from scipy.special import beta as beta_fun \n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# moment-based inference\n", + "def MomentInference(vals, export_moments=False):\n", + " # code from Anton Larsson's R implementation\n", + " from scipy import stats # needs imports inside function when run in ipyparallel\n", + " import numpy as np\n", + " m1 = float(np.mean(vals))\n", + " m2 = float(sum(vals*(vals - 1))/len(vals))\n", + " m3 = float(sum(vals*(vals - 1)*(vals - 2))/len(vals))\n", + " \n", + " # sanity check on input (e.g. need at least on expression level)\n", + " if sum(vals) == 0: return np.nan\n", + " if m1 == 0: return np.nan\n", + " if m2 == 0: return np.nan\n", + " \n", + " r1=m1\n", + " r2=m2/m1\n", + " r3=m3/m2\n", + " \n", + " if (r1*r2-2*r1*r3 + r2*r3) == 0: return np.nan\n", + " if ((r1*r2 - 2*r1*r3 + r2*r3)*(r1-2*r2+r3)) == 0: return np.nan\n", + " if (r1 - 2*r2 + r3) == 0: return np.nan\n", + " \n", + " lambda_est = (2*r1*(r3-r2))/(r1*r2-2*r1*r3 + r2*r3)\n", + " mu_est = (2*(r3-r2)*(r1-r3)*(r2-r1))/((r1*r2 - 2*r1*r3 + r2*r3)*(r1-2*r2+r3))\n", + " v_est = (2*r1*r3 - r1*r2 - r2*r3)/(r1 - 2*r2 + r3)\n", + " \n", + " if export_moments:\n", + " return np.array([lambda_est, mu_est, v_est, r1, r2, r3])\n", + " \n", + " return np.array([lambda_est, mu_est, v_est])\n", + "def MaximumLikelihood(vals, export_asymp_ci = False, fix = 0, export_fun = False):\n", + " from scipy.interpolate import interp1d\n", + " from scipy.optimize import minimize\n", + " from scipy import special\n", + " from scipy.stats import poisson,norm\n", + " from scipy.special import j_roots\n", + " from scipy.special import beta as beta_fun \n", + " import numpy as np\n", + " if len(vals) == 0:\n", + " return np.array([np.nan, np.nan, np.nan])\n", + " def dBP(at, alpha, bet, lam):\n", + " at.shape = (len(at), 1)\n", + " np.repeat(at, 50, axis = 1)\n", + " def fun(at, m):\n", + " if(max(m) < 1e6):\n", + " return(poisson.pmf(at,m))\n", + " else:\n", + " return(norm.pdf(at,loc=m,scale=sqrt(m)))\n", + " \n", + " x,w = j_roots(50,alpha = bet - 1, beta = alpha - 1)\n", + " gs = np.sum(w*fun(at, m = lam*(1+x)/2), axis=1)\n", + " prob = 1/beta_fun(alpha, bet)*2**(-alpha-bet+1)*gs\n", + " return(prob)\n", + " def LogLikelihood(x, vals):\n", + " kon = x[0]\n", + " koff = x[1]\n", + " ksyn = x[2]\n", + " return(-np.sum(np.log( dBP(vals,kon,koff,ksyn) + 1e-10) ) )\n", + " x0 = MomentInference(vals)\n", + " if np.isnan(x0).any():\n", + " x0 = np.array([10,10,10])\n", + " bnds = ((1e-3,1e3),(1e-3,1e3), (1, 1e10))\n", + " vals_ = np.copy(vals) # Otherwise the structure is violated.\n", + " try:\n", + " ll = minimize(LogLikelihood, x0, args = (vals_), method='L-BFGS-B', bounds = bnds)\n", + " except:\n", + " if export_fun:\n", + " return np.array([np.nan,np.nan,np.nan]), np.nan\n", + " return np.array([np.nan,np.nan,np.nan])\n", + " #se = ll.hess_inv.todense().diagonal()\n", + " if export_fun:\n", + " return ll.x, ll.fun\n", + " estim = ll.x\n", + " return estim\n", + "def ProfileLikelihood3(vals, alph = 0.05):\n", + " from scipy.interpolate import interp1d\n", + " from scipy.optimize import minimize, fsolve\n", + " from scipy import special\n", + " from scipy.stats import poisson,norm, chi2\n", + " from scipy.special import j_roots\n", + " from scipy.special import beta as beta_fun\n", + " import numpy as np\n", + " def dBP(at, alpha, bet, lam):\n", + " at.shape = (len(at), 1)\n", + " np.repeat(at, 50, axis = 1)\n", + " def fun(at, m):\n", + " if(max(m) < 1e6):\n", + " return(poisson.pmf(at,m))\n", + " else:\n", + " return(norm.pdf(at,loc=m,scale=sqrt(m)))\n", + " x,w = j_roots(50,alpha = bet - 1, beta = alpha - 1)\n", + " gs = np.sum(w*fun(at, m = lam*(1+x)/2), axis=1)\n", + " prob = 1/beta_fun(alpha, bet)*2**(-alpha-bet+1)*gs\n", + " return(prob)\n", + " def ll_kon(x, l, obs):\n", + " mu = x[0]\n", + " v = x[1]\n", + " return(-np.sum(np.log(dBP(obs,l,mu,v) + 1e-10)))\n", + " def ll_burst_size(x, burst_size, obs):\n", + " l = x[0]\n", + " v = x[1]\n", + " mu = v/burst_size\n", + " return(-np.sum(np.log(dBP(obs,l,mu,v) + 1e-10)))\n", + " def minll_kon(x, kon, obs):\n", + " bnds = ((1e-3, 1e3), (1,1e10))\n", + " res = minimize(ll_kon, x, args = (kon,obs), method='L-BFGS-B', bounds = bnds)\n", + " ll = res.fun\n", + " x0 = res.x\n", + " return ll, x0\n", + " def minll_burst_size(x, burst_size, obs):\n", + " bnds = ((1e-3, 1e3), (1,1e6))\n", + " res = minimize(ll_burst_size, x, args = (burst_size,obs), method='L-BFGS-B', bounds = bnds)\n", + " ll = res.fun\n", + " x0 = res.x\n", + " return ll, x0\n", + " def get_h(param):\n", + " x = np.log10(param)\n", + " h = 10**(x-2)\n", + " return(h)\n", + " \n", + " def kon_ll(vals,start_estim):\n", + " cutoff = chi2.ppf(1-alph, 1)/2\n", + " x0 = [start_estim[1], start_estim[2]]\n", + " bnds = ((1e-3, 1e3), (1,1e10))\n", + " N = 100\n", + " start = start_estim[0]\n", + " res = minimize(ll_kon, x0, args = (start,vals), method='L-BFGS-B', bounds = bnds)\n", + " h = get_h(start)\n", + " h = 5*h\n", + " ll_p = res.fun\n", + " ll_l = np.zeros(N)\n", + " kon_l = np.array([])\n", + " try:\n", + " for i in range(N):\n", + " kon = start - h*i\n", + " if kon <= 0:\n", + " break\n", + " kon_l = np.append(kon_l, kon)\n", + " try:\n", + " res = minimize(ll_kon, res.x, args = (kon,vals), method='L-BFGS-B', bounds = bnds)\n", + " except ValueError:\n", + " break\n", + " ll_l[i] = res.fun\n", + " if (2*(ll_l[i] - min(ll_l[ll_l > 0])) > cutoff + 0.5) and (ll_l[i] > ll_l[i-1]):\n", + " break\n", + " except ValueError:\n", + " return np.array([minimum,np.nan,np.nan]), np.nan\n", + " \n", + " ll_l = ll_l[:i+1]\n", + " ll_l = ll_l[::-1]\n", + " kon_l = kon_l[::-1] \n", + " res = minimize(ll_kon, x0, args = (start,vals), method='L-BFGS-B', bounds = bnds)\n", + " ll_u = np.zeros(N)\n", + " kon_u = np.array([])\n", + " try:\n", + " for j in range(N):\n", + " kon = start + h*j\n", + " kon_u = np.append(kon_u, kon)\n", + " try:\n", + " res = minimize(ll_kon, res.x, args = (kon,vals), method='L-BFGS-B', bounds = bnds)\n", + " except ValueError:\n", + " break\n", + " ll_u[j] = res.fun\n", + " if (2*(ll_u[j] - min(ll_u[ll_u > 0])) > cutoff + 0.5) and (ll_u[j] > ll_u[j-1]):\n", + " break\n", + " except ValueError:\n", + " return np.array([minimum,np.nan,np.nan]), np.nan\n", + " \n", + " ll_u = ll_u[:j+1]\n", + " \n", + " ll = np.concatenate((ll_l[:-1],np.array([ll_p]),ll_u[1:]))\n", + " kon_indexed = np.concatenate((kon_l[:-1],np.array([start]),kon_u[1:])).squeeze()\n", + " \n", + " ll_ratio = 2*(ll - min(ll)).squeeze()\n", + " \n", + " minimum_idx = np.argmin(ll_ratio)\n", + " \n", + " ll_right_side = ll_ratio[minimum_idx:]\n", + " ll_left_side = ll_ratio[:minimum_idx]\n", + " \n", + " minimum = kon_indexed[minimum_idx]\n", + " kon_right_side = kon_indexed[minimum_idx:]\n", + " kon_left_side = kon_indexed[:minimum_idx]\n", + " try:\n", + " f_1 = interp1d(ll_left_side,kon_left_side, kind='cubic')\n", + " f_2 = interp1d(ll_right_side,kon_right_side , kind='cubic')\n", + " res = np.array([minimum, f_1(cutoff), f_2(cutoff)])\n", + " return res, kon_indexed, ll_ratio\n", + " except (ValueError,np.linalg.linalg.LinAlgError, TypeError):\n", + " return np.array([minimum,np.nan,np.nan]), kon_indexed, ll_ratio\n", + "\n", + " def burst_size_ll(vals, start_estim):\n", + " cutoff = chi2.ppf(1-alph, 1)/2\n", + " x0 = [start_estim[0], start_estim[2]]\n", + " bnds = ((1e-3, 1e3), (1,1e10))\n", + " N = 100\n", + " start = start_estim[2]/start_estim[1]\n", + " res = minimize(ll_burst_size, x0, args = (start,vals), method='L-BFGS-B', bounds = bnds)\n", + " h = get_h(start)\n", + " h = 3*h\n", + " ll_p = res.fun\n", + " ll_l = np.zeros(N)\n", + " burst_size_l = np.array([])\n", + " try:\n", + " for i in range(N):\n", + " burst_size = start - h*i\n", + " if burst_size <= 0:\n", + " break\n", + " burst_size_l = np.append(burst_size_l, burst_size)\n", + " try:\n", + " res = minimize(ll_burst_size, res.x, args = (burst_size,vals), method='L-BFGS-B', bounds = bnds)\n", + " except ValueError:\n", + " break\n", + " ll_l[i] = res.fun\n", + " if (2*(ll_l[i] - min(ll_l[ll_l > 0])) > cutoff + 0.5) and (ll_l[i] > ll_l[i-1]):\n", + " break\n", + " except ValueError:\n", + " return np.array([minimum,np.nan,np.nan]), np.nan\n", + " ll_l = ll_l[:i+1]\n", + " ll_l = ll_l[::-1]\n", + " burst_size_l = burst_size_l[::-1] \n", + " res = minimize(ll_burst_size, x0, args = (start,vals), method='L-BFGS-B', bounds = bnds)\n", + " ll_u = np.zeros(N)\n", + " burst_size_u = np.array([])\n", + " try:\n", + " for j in range(N):\n", + " burst_size = start + h*j\n", + " burst_size_u = np.append(burst_size_u, burst_size)\n", + " try:\n", + " res = minimize(ll_burst_size, res.x, args = (burst_size,vals), method='L-BFGS-B', bounds = bnds)\n", + " except ValueError:\n", + " break\n", + " ll_u[j] = res.fun\n", + " if (2*(ll_u[j] - min(ll_u[ll_u > 0])) > cutoff + 0.5) and (ll_u[j] > ll_u[j-1]):\n", + " break\n", + " except ValueError:\n", + " return np.array([minimum,np.nan,np.nan]), np.nan\n", + " \n", + " ll_u = ll_u[:j+1]\n", + " \n", + " ll = np.concatenate((ll_l[:-1],np.array([ll_p]),ll_u[1:]))\n", + " burst_size_indexed = np.concatenate((burst_size_l[:-1],np.array([start]),burst_size_u[1:])).squeeze()\n", + " \n", + " ll_ratio = 2*(ll - min(ll)).squeeze()\n", + " \n", + " minimum_idx = np.argmin(ll_ratio)\n", + " \n", + " ll_right_side = ll_ratio[minimum_idx:]\n", + " ll_left_side = ll_ratio[:minimum_idx]\n", + " \n", + " minimum = burst_size_indexed[minimum_idx]\n", + " burst_size_right_side = burst_size_indexed[minimum_idx:]\n", + " burst_size_left_side = burst_size_indexed[:minimum_idx]\n", + " try:\n", + " f_1 = interp1d(ll_left_side,burst_size_left_side, kind='linear')\n", + " f_2 = interp1d(ll_right_side,burst_size_right_side , kind='linear')\n", + " res = np.array([minimum, f_1(cutoff), f_2(cutoff)])\n", + " return res, burst_size_indexed, ll_ratio\n", + " except (ValueError,np.linalg.linalg.LinAlgError, TypeError):\n", + " return np.array([minimum,np.nan,np.nan]), burst_size_indexed, ll_ratio\n", + " vals_ = np.copy(vals)\n", + " start_estim = MaximumLikelihood(vals_)\n", + " try:\n", + " res_kon, kon_idx, kon_ll_ratio = kon_ll(vals_, start_estim)\n", + " res_burst_size, bs_idx, bs_ll_ratio = burst_size_ll(vals_,start_estim)\n", + " except BaseException:\n", + " return np.array([np.nan,np.nan,np.nan]), np.nan, np.array([np.nan,np.nan,np.nan]), np.nan\n", + " return res_kon, kon_idx, kon_ll_ratio, res_burst_size, bs_idx, bs_ll_ratio" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from numpy.random import beta, poisson\n", + "def sim_beta_poisson(kon,koff,ksyn=100, size=100):\n", + " \"Generate simulated single-cell RNA-seq data according to the two-state model and with parameters kon, koff, ksyn\"\n", + " v = beta(kon, koff, size)\n", + " return poisson(v*ksyn)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "np.random.seed(12039213)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "X = sim_beta_poisson(0.5,0.5,20, 200)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "Y = ProfileLikelihood3(X)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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2cR4qoF2c4eHhrFix4pLtxYoVIyXl75nnzp71XPzz589n7ty5LFmyhDVr1tCi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\nrRFTiW4pCaQ2SSK1aSJdGydQPcbN37zGhAa3/fTcJL1thax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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(7,5))\n", + "plt.plot(Y[1], Y[2])\n", + "plt.plot([0.41, 0.66], [1.92, 1.92], '-', c='r')\n", + "plt.plot([0.424, 0.424], [1.92,0], '--', c='r')\n", + "plt.plot([0.65, 0.65], [1.92,0], '--', c='r')\n", + "plt.plot([0.5],[0.125], 'o', c = 'g')\n", + "plt.title('Profile likelihood illustration')\n", + "plt.xlabel(r'Burst Frequency')\n", + "plt.ylabel('Transformed likelihood (Lower values are more likely)')\n", + "plt.text(0.45, 2.1, r'Cutoff at $\\chi_1^2(0.05)/2 = 1.92$')\n", + "plt.text(0.5, 1.3, r'True Burst Frequency: 0.5')\n", + "plt.text(.5,1,r'95%% CI: [%s, %s]' % (np.round(Y[0][1],3), np.round(Y[0][2],3)))\n", + "plt.savefig('figures/ExtDataFig1b.pdf', dpi=100)\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Fig 1b.ipynb b/Fig 1b.ipynb new file mode 100644 index 0000000..cb7902c --- /dev/null +++ b/Fig 1b.ipynb @@ -0,0 +1,540 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n" + ] + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "import pandas as pd\n", + "import numpy as np" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# How the data is simulated" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from numpy.random import poisson,beta\n", + "n = 10\n", + "array_alpha_kon = np.ones((n,n))\n", + "array_alpha_koff = np.ones((n,n))\n", + "array_width_kon = np.ones((n,n))\n", + "array_width_koff = np.ones((n,n))\n", + "array_nan_kon = np.ones((n,n))\n", + "array_nan_koff = np.ones((n,n))\n", + "kon = np.logspace(-3,1,n)\n", + "koff = np.logspace(-1,2, n)\n", + "mesh_kon, mesh_koff = np.meshgrid(kon,koff,sparse = True)\n", + "array_p = np.ones((n,n,30, 140))\n", + "array_x = np.ones((n,n,30, 140))\n", + "for i in range(n):\n", + " for k in range(n):\n", + " for j in range(30):\n", + " array_p[i,k,j,] = beta(kon[i], koff[k], 140)\n", + " array_x[i,k,j,] = poisson(100*array_p[i,k,j,])" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "s = array_x.shape\n", + "expr_dict = {}\n", + "for i in range(s[0]):\n", + " for k in range(s[1]):\n", + " for j in range(s[2]):\n", + " expr_dict['expr_{}_{}_{}'.format(i,k,j)] = array_x[i,k,j,]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "#I saved the result to this .csv file and then did the inference. But did not set a seed. Woohoo.\n", + "#pd.DataFrame(expr_dict).T.to_csv('data/simulated_expr.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "sim_df = pd.read_pickle('data/simulated_expr_PL.pkl')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "kon_group = pd.Series([idx.split('_')[1] for idx in sim_df.index], index=sim_df.index)\n", + "kon_group.name = 'kon_group'\n", + "koff_group = pd.Series([idx.split('_')[2] for idx in sim_df.index], index=sim_df.index)\n", + "koff_group.name = 'koff_group'\n", + "sim_df = sim_df.join(kon_group)\n", + "sim_df = sim_df.join(koff_group)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "2.8295616938487402\n", + "0\n", + "\n", + "2.9365004588089736\n", + "1\n", + "\n", + "2.9319284534719277\n", + "2\n", + "\n", + "2.9797045332164043\n", + "3\n", + "\n", + "2.497262957773357\n", + "4\n", + "\n", + "4.660541249273583\n", + "5\n", + "\n", + "nan\n", + "6\n", + "\n", + "4.767803513085894\n", + "7\n", + "\n", + "nan\n", + "8\n", + "\n", + "nan\n", + "9\n", + "\n", + "1.9515933739118618\n", + "0\n", + "\n", + "2.179338039655786\n", + "1\n", + "\n", + "2.314735355914266\n", + "2\n", + "\n", + "2.3662529069012606\n", + "3\n", + "\n", + "2.6715141619151437\n", + "4\n", + "\n", + "3.2946698977429567\n", + "5\n", + "\n", + "4.2084989277522045\n", + "6\n", + "\n", + "4.115046419792105\n", + "7\n", + "\n", + "nan\n", + "8\n", + "\n", + "nan\n", + "9\n", + "\n", + "1.272011849080847\n", + "0\n", + "\n", + "1.3144238467188984\n", + "1\n", + "\n", + "1.6226615690212556\n", + "2\n", + "\n", + "1.7542267986137825\n", + "3\n", + "\n", + "1.9883200955475793\n", + "4\n", + "\n", + "2.6906181184973663\n", + "5\n", + "\n", + "2.5711126354392038\n", + "6\n", + "\n", + "nan\n", + "7\n", + "\n", + "4.8861191845572165\n", + "8\n", + "\n", + "nan\n", + "9\n", + "\n", + "0.7750237348686639\n", + "0\n", + "\n", + "0.7642021195139035\n", + "1\n", + "\n", + "0.8157934733875184\n", + "2\n", + "\n", + "0.9734145308452582\n", + "3\n", + "\n", + "1.1522870450629261\n", + "4\n", + "\n", + "1.3917880662351583\n", + "5\n", + "\n", + "1.618001237393996\n", + "6\n", + "\n", + "1.7375887463234296\n", + "7\n", + "\n", + "2.070788587830549\n", + "8\n", + "\n", + "nan\n", + "9\n", + "\n", + "0.5647841677369496\n", + "0\n", + "\n", + "0.520486474165362\n", + "1\n", + "\n", + "0.5292237314746969\n", + "2\n", + "\n", + "0.5723660884253486\n", + "3\n", + "\n", + "0.6517515140061574\n", + "4\n", + "\n", + "0.7766950419078242\n", + "5\n", + "\n", + "1.059195545922697\n", + "6\n", + "\n", + "1.3395881078373384\n", + "7\n", + "\n", + "1.67548617150619\n", + "8\n", + "\n", + "2.3567930874777767\n", + "9\n", + "\n", + "0.5051633435871269\n", + "0\n", + "\n", + "0.4186183957588036\n", + "1\n", + "\n", + "0.3901966337943147\n", + "2\n", + "\n", + "0.4012171953331778\n", + "3\n", + "\n", + "0.4421369405804743\n", + "4\n", + "\n", + "0.5119281404057502\n", + "5\n", + "\n", + "0.6523369249817044\n", + "6\n", + "\n", + "0.8577051442734706\n", + "7\n", + "\n", + "1.2449992637881646\n", + "8\n", + "\n", + "1.6628640658101457\n", + "9\n", + "\n", + "0.6027728412324184\n", + "0\n", + "\n", + "0.4506482272199379\n", + "1\n", + "\n", + "0.37542974855079153\n", + "2\n", + "\n", + "0.35570092536880565\n", + "3\n", + "\n", + "0.3716308381130151\n", + "4\n", + "\n", + "0.4184587265852651\n", + "5\n", + "\n", + "0.4890077864711812\n", + "6\n", + "\n", + "0.6265795851675777\n", + "7\n", + "\n", + "1.022942779099793\n", + "8\n", + "\n", + "1.2851596999385149\n", + "9\n", + "\n", + "0.9131636288048204\n", + "0\n", + "\n", + "0.6547115046475968\n", + "1\n", + "\n", + "0.5067496999237906\n", + "2\n", + "\n", + "0.4307330486261556\n", + "3\n", + "\n", + "0.41633289872677115\n", + "4\n", + "\n", + "0.4740418325044004\n", + "5\n", + "\n", + "0.4490174627162145\n", + "6\n", + "\n", + "0.5825140991734574\n", + "7\n", + "\n", + "0.8127568487084482\n", + "8\n", + "\n", + "1.3076127878641222\n", + "9\n", + "\n", + "1.9039460669356296\n", + "0\n", + "\n", + "1.2508290351508822\n", + "1\n", + "\n", + "0.8589123308930819\n", + "2\n", + "\n", + "0.6774279317765505\n", + "3\n", + "\n", + "0.6549964755770278\n", + "4\n", + "\n", + "0.6770363561755295\n", + "5\n", + "\n", + "0.6924380224164295\n", + "6\n", + "\n", + "0.7594061998408701\n", + "7\n", + "\n", + "0.8542717670987073\n", + "8\n", + "\n", + "1.2220351887875374\n", + "9\n", + "\n", + "3.4856792968843004\n", + "0\n", + "\n", + "3.4988993250410765\n", + "1\n", + "\n", + "2.6416797247659867\n", + "2\n", + "\n", + "2.2685623806457653\n", + "3\n", + "\n", + "1.532915394257101\n", + "4\n", + "\n", + "1.5007357931058343\n", + "5\n", + "\n", + "1.2690724692483693\n", + "6\n", + "\n", + "1.1105801986722237\n", + "7\n", + "\n", + "1.033170171540762\n", + "8\n", + "\n", + "1.5802547318488878\n", + "9\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/site-packages/numpy/core/fromnumeric.py:2920: RuntimeWarning: Mean of empty slice.\n", + " out=out, **kwargs)\n", + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/site-packages/numpy/core/_methods.py:85: RuntimeWarning: invalid value encountered in double_scalars\n", + " ret = ret.dtype.type(ret / rcount)\n" + ] + } + ], + "source": [ + "n=10\n", + "array_width_bf = np.ones((n,n))\n", + "array_width_bs = np.ones((n,n))\n", + "for kon_idx, kon_df in sim_df.groupby('kon_group'):\n", + " for koff_idx, koff_df in kon_df.groupby('koff_group'):\n", + " mean_width = np.mean([(p[2]-p[1])/p[0] for p in koff_df[1] if all(~np.isnan(p))])\n", + " if mean_width > 10000:\n", + " mean_width = np.nan\n", + " print(type(kon_idx))\n", + " print(mean_width)\n", + " print(koff_idx)\n", + " array_width_bf[int(kon_idx), int(koff_idx)] = mean_width" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "PL_CIs = pd.read_pickle('data/SS3_cast_UMIs_concat_PL.pkl')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "bf = pd.Series([p[0] for p in PL_CIs[0]], index=PL_CIs.index)\n", + "bs = pd.Series([p[2]/p[1] for p in PL_CIs[0]], index=PL_CIs.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from scipy.interpolate import interp1d\n", + "f_bf = interp1d( np.logspace(-3,1,100), np.linspace(0,9,100), fill_value='extrapolate')\n", + "f_bs = interp1d(100/np.logspace(-1,2, 100)[::-1], np.linspace(0,9,100),fill_value='extrapolate')\n", + "kon = np.logspace(-3,1,n)\n", + "koff = np.logspace(-1,2, n) " + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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VPXVTp2Pfuom6qdPDrl2/f9Vd99MSCFGq1+8M8Ri1Z5GNSCUyI6TYO3FBEtjRy0ZTkTWI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\npbqZrrGOSHMp5i0bieQVSDWpHge6eMowIUoJ5uSia2slmpOHIhhC7XK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h6C9/RNvTjdbt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\nyGmdpWDFpsa0H0WpZtQCKxE3/fEumNInt8jCAuznza1ZA77wfr8llc2y8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yyX\nuz9v4lTJLsQ9ORx41r0HfwH6BP1ePOd+h9yiEOPck9DvDPBXz/N+OPXn3sVpNisFuCffcH//f8UJ\niLjQM9eDBHyfyV/AAu+Jb/xv8QiY/b3gWEAGJzjFfr7vFvieBH5nvL+fsHmr7UdLSSmKoigVSSXu\ngSmKoiiKCpiiKIpSmaiAKYqiKBWJCpiiKIpSkaiAKYqiKBWJCpiiKIpSkaiAKYqiKBXJ/wejEKYc\nfSZAMQAAAABJRU5ErkJggg==\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "fig = plt.figure(figsize=(7,7))\n", + "plt.contourf(np.fliplr(np.log2(array_width_bf)), cmap='Blues')\n", + "plt.colorbar()\n", + "plt.scatter(f_bs(bs), f_bf(bf), s=1, c='red')\n", + "plt.yticks(np.arange(10), np.round(kon,3) )\n", + "plt.xticks(np.arange(10), np.round(100/koff[::-1],1) )\n", + "plt.xlim(0,9)\n", + "plt.savefig('figures/Fig1b.pdf')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Figure 1a.ipynb b/Figure 1a.ipynb new file mode 100644 index 0000000..333508b --- /dev/null +++ b/Figure 1a.ipynb @@ -0,0 +1,252 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "from scipy import stats\n", + "from numpy import mean\n", + "from numpy.random import beta, poisson\n", + "from scipy.special import j_roots\n", + "from scipy.special import beta as beta_fun\n", + "from matplotlib import pyplot as plt\n", + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "test = pd.read_pickle('data/SS3_c57_UMIs_concat_vs_SS3_cast_UMIs_concat_TEST.pkl')\n", + "c57 = pd.read_csv('data/SS3_c57_UMIs_concat.csv', index_col=0)\n", + "cast = pd.read_csv('data/SS3_cast_UMIs_concat.csv', index_col=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# moment-based inference\n", + "def MomentInference(vals, export_moments=False):\n", + " # code from Anton Larsson's R implementation\n", + " from scipy import stats # needs imports inside function when run in ipyparallel\n", + " import numpy as np\n", + " m1 = float(np.mean(vals))\n", + " m2 = float(sum(vals*(vals - 1))/len(vals))\n", + " m3 = float(sum(vals*(vals - 1)*(vals - 2))/len(vals))\n", + " \n", + " # sanity check on input (e.g. need at least on expression level)\n", + " if sum(vals) == 0: return np.nan\n", + " if m1 == 0: return np.nan\n", + " if m2 == 0: return np.nan\n", + " \n", + " r1=m1\n", + " r2=m2/m1\n", + " r3=m3/m2\n", + " \n", + " if (r1*r2-2*r1*r3 + r2*r3) == 0: return np.nan\n", + " if ((r1*r2 - 2*r1*r3 + r2*r3)*(r1-2*r2+r3)) == 0: return np.nan\n", + " if (r1 - 2*r2 + r3) == 0: return np.nan\n", + " \n", + " lambda_est = (2*r1*(r3-r2))/(r1*r2-2*r1*r3 + r2*r3)\n", + " mu_est = (2*(r3-r2)*(r1-r3)*(r2-r1))/((r1*r2 - 2*r1*r3 + r2*r3)*(r1-2*r2+r3))\n", + " v_est = (2*r1*r3 - r1*r2 - r2*r3)/(r1 - 2*r2 + r3)\n", + " \n", + " if export_moments:\n", + " return np.array([lambda_est, mu_est, v_est, r1, r2, r3])\n", + " \n", + " return np.array([lambda_est, mu_est, v_est])\n", + "def MaximumLikelihood(vals, export_asymp_ci = False, fix = 0, export_fun = False):\n", + " from scipy.interpolate import interp1d\n", + " from scipy.optimize import minimize\n", + " from scipy import special\n", + " from scipy.stats import poisson,norm\n", + " from scipy.special import j_roots\n", + " from scipy.special import beta as beta_fun \n", + " import numpy as np\n", + " if len(vals) == 0:\n", + " return np.array([np.nan, np.nan, np.nan])\n", + " def dBP(at, alpha, bet, lam):\n", + " at.shape = (len(at), 1)\n", + " np.repeat(at, 50, axis = 1)\n", + " def fun(at, m):\n", + " if(max(m) < 1e6):\n", + " return(poisson.pmf(at,m))\n", + " else:\n", + " return(norm.pdf(at,loc=m,scale=sqrt(m)))\n", + " \n", + " x,w = j_roots(50,alpha = bet - 1, beta = alpha - 1)\n", + " gs = np.sum(w*fun(at, m = lam*(1+x)/2), axis=1)\n", + " prob = 1/beta_fun(alpha, bet)*2**(-alpha-bet+1)*gs\n", + " return(prob)\n", + " def LogLikelihood(x, vals):\n", + " kon = x[0]\n", + " koff = x[1]\n", + " ksyn = x[2]\n", + " return(-np.sum(np.log( dBP(vals,kon,koff,ksyn) + 1e-10) ) )\n", + " x0 = MomentInference(vals)\n", + " if np.isnan(x0).any():\n", + " x0 = np.array([10,10,10])\n", + " bnds = ((1e-3,1e3),(1e-3,1e3), (1, 1e10))\n", + " vals_ = np.copy(vals) # Otherwise the structure is violated.\n", + " try:\n", + " ll = minimize(LogLikelihood, x0, args = (vals_), method='L-BFGS-B', bounds = bnds)\n", + " except:\n", + " if export_fun:\n", + " return np.array([np.nan,np.nan,np.nan]), np.nan\n", + " return np.array([np.nan,np.nan,np.nan])\n", + " #se = ll.hess_inv.todense().diagonal()\n", + " if export_fun:\n", + " return ll.x, ll.fun\n", + " estim = ll.x\n", + " return estim" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "cells = 222" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def dBP(at, alpha, bet, lam):\n", + " at.shape = (len(at),1)\n", + " np.repeat(at, 50, axis = 1)\n", + " def fun(at, m):\n", + " if(max(m) < 1e6):\n", + " return(stats.poisson.pmf(at,m))\n", + " else:\n", + " return(stats.norm.pdf(at,loc=m,scale=sqrt(m)))\n", + " if alpha <= 0 or bet <= 0:\n", + " return np.nan\n", + " x,w = j_roots(50,alpha = bet-1, beta = alpha - 1)\n", + " gs = np.sum(w*fun(at, m = lam*(1+x)/2), axis=1)\n", + " prob = 1/beta_fun(alpha, bet)*2**(-alpha-bet+1)*gs\n", + " return(prob)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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IvHsUDqcU5qsWnLDgMN699l3CQ8IZvWI09+/P/ZhFY4wpjlJSU+jyfhdmbZpF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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "gene = 'Mbnl2'\n", + "mat = c57.loc[gene][pd.notnull(c57.loc[gene])]\n", + "pat = cast.loc[gene][pd.notnull(cast.loc[gene])]\n", + "fig = plt.figure(figsize=(12,3))\n", + "plt.subplot(121)\n", + "tot_kon,tot_koff, tot_ksyn = test.loc[gene][0]\n", + "plt.hist(mat, bins=40, label='c57', color='orange')\n", + "plt.plot(cells*dBP(np.arange(35), tot_kon, tot_koff, tot_ksyn),'g--',linewidth=2)\n", + "plt.xlabel(\"Maternal Expression\")\n", + "plt.ylabel(\"Cells\")\n", + "plt.title(\"kon=%.2f, koff=%.2f, ksyn=%.2f\" % (tot_kon, tot_koff, tot_ksyn))\n", + "plt.legend(loc='best')\n", + "plt.subplot(122)\n", + "tot_kon,tot_koff, tot_ksyn = test.loc[gene][1]\n", + "plt.hist(pat, bins=32, label='Cast', color='blue')\n", + "plt.plot(cells*dBP(np.arange(35), tot_kon, tot_koff, tot_ksyn), 'g--',linewidth=2)\n", + "plt.xlabel(\"Paternal Expression\")\n", + "plt.ylabel(\"Cells\")\n", + "plt.legend(loc='best')\n", + "plt.title(\"kon=%.2f, koff=%.2f, ksyn=%.2f\" % (tot_kon, tot_koff, tot_ksyn))\n", + "plt.savefig(\"figures/Fig1a_{}_allelic.pdf\".format(gene))\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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AJ8A30xiDiIi0UmlLUO4+EbDtbD42Xa8rIiK5QT1JiIhIVlKCEhGRrKQEJSIiWUkJSkRE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\nxRfXH9gdWAn8O+F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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "tot_kon, tot_koff, tot_ksyn = MaximumLikelihood(mat+pat)\n", + "plt.hist(mat+pat, bins=40, label='total', color='black')\n", + "plt.plot(cells*dBP(np.arange(60), tot_kon, tot_koff, tot_ksyn),'g--',linewidth=2)\n", + "plt.xlabel(\"Total Expression\")\n", + "plt.ylabel(\"Cells\")\n", + "plt.title(\"kon=%.2f, koff=%.2f, ksyn=%.2f\" % (tot_kon, tot_koff, tot_ksyn))\n", + "plt.legend(loc='best')\n", + "plt.tight_layout()\n", + "plt.savefig('figures/Fig1a_{}_total.pdf'.format(gene))\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Figure 1c-d, 1g and ExtDataFig 3f.ipynb b/Figure 1c-d, 1g and ExtDataFig 3f.ipynb new file mode 100644 index 0000000..229e605 --- /dev/null +++ b/Figure 1c-d, 1g and ExtDataFig 3f.ipynb @@ -0,0 +1,215 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Figure 1b, 1c, 1d, 1g and ExtDataFig 3f." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "ML_concat = pd.read_pickle('data/SS3_cast_UMIs_concat_ML.pkl')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "ML_concat = ML_concat[ML_concat[1]][0]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "cast_bs_UMI = pd.Series([gene[2]/gene[1] for gene in ML_concat], index=ML_concat.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "cast_bf_UMI = pd.Series([gene[0] for gene in ML_concat], index=ML_concat.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "cast_me_UMI = pd.Series([gene[2]*(gene[0]/(gene[0]+gene[1])) for gene in ML_concat], index=ML_concat.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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l5IQkuWEJXhDaMnlliLhDttLkCsgWkoglaRIKcfbvDievaRZrF5VwZfcHmfzF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+91TNXHO1g7/wP6zyxh8AWfn6b+SRw6jmRmsZTyPSFEvz0270tpoQJlDD7jMNSw95dQNgmYDOQI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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.colors as colors\n", + "plt.scatter(np.log10(cast_bs_UMI), np.log10(cast_bf_UMI), s=5, c=cast_me_UMI, cmap='magma_r', norm=colors.LogNorm(vmin=min(cast_me_UMI), vmax=max(cast_me_UMI)))\n", + "plt.colorbar()\n", + "plt.xlabel('Burst size')\n", + "plt.ylabel('Burst frequency')\n", + "plt.savefig('figures/ExtDataFig3f.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Jvp9k2rMDlnp/thrGrXWp9+mxSa5Jcnd7Pmaafk+2/XlLkkU74WG2/ZPkGUkua8tvTLJ+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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist(np.log10(cast_bf_UMI), bins=40)\n", + "plt.xlabel(r'Burst frequency (log$_{10}$)')\n", + "plt.savefig('figures/Fig1c.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist(np.log10(cast_bs_UMI), bins=40)\n", + "plt.xlabel(r'Burst size (log$_{10}$)')\n", + "plt.savefig('figures/Fig1d.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "cast_koff_UMI = pd.Series([gene[1] for gene in ML_concat], index=ML_concat.index)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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/jjpd3ZocN5+Fli/x52pWfHNzM3WZEEubuCZ4nqduCeFmo1wuh91uBwCUlZVhYGAA7e3t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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(np.arange(-2,2,0.5),np.arange(-2,2,0.5), 'g--')\n", + "plt.scatter(np.log10(cast_koff_UMI), np.log10(cast_bf_UMI), s=1, c='grey')\n", + "plt.savefig('figures/Fig1g.pdf')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Figure 1e, 1f.ipynb b/Figure 1e, 1f.ipynb new file mode 100644 index 0000000..f34fc1a --- /dev/null +++ b/Figure 1e, 1f.ipynb @@ -0,0 +1,143 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy.stats import spearmanr" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "DR_ES = pd.read_csv('data/slam_seq.csv', sep=';')\n", + "\n", + "cast = pd.read_pickle('data/SS3_cast_UMIs_mESC_ML.pkl')\n", + "\n", + "cast = cast[cast[1]][0]\n", + "\n", + "cast = cast[~cast.index.duplicated(keep='first')]\n", + "\n", + "DR_ES.index = DR_ES['Name']\n", + "\n", + "DR_ES = DR_ES[~DR_ES.index.duplicated(keep='first')]\n", + "\n", + "DR_ES = DR_ES.dropna(how='any')\n", + "\n", + "DR_ES['decay'] = np.log(2)/DR_ES['Half-life (h)']\n", + "\n", + "bf = pd.Series([gene[0] for gene in cast], index=cast.index)\n", + "\n", + "DR_ES_scRNA = DR_ES.reindex(cast.index)\n", + "\n", + "decay_ES = DR_ES_scRNA['decay']\n", + "decay_ES = decay_ES.replace([np.inf, 0], np.nan).dropna()\n", + "decay_ES = decay_ES[~decay_ES.index.duplicated(keep='first')]\n", + "decay_ES = decay_ES[decay_ES > 0]\n", + "decay_ES = decay_ES.dropna()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "SpearmanrResult(correlation=0.8429552739198909, pvalue=0.0)\n" + ] + }, + { + "data": { + "image/png": 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Uux8iGexEf23gUDDu8yIgnNhIECAIwi1nuKOC9WChZ18PGaaMIYMBPRV+qN7B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1xvzK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\n8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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8,8))\n", + "bf_absolute = np.log10((bf*decay_ES).dropna())\n", + "bf_relative = np.log10(bf[decay_ES.index].dropna())\n", + "plt.scatter(bf_absolute,bf_relative , s=1)\n", + "plt.scatter(bf_absolute[np.argsort(decay_ES[bf_relative.index])[:50]], bf_relative[np.argsort(decay_ES[bf_relative.index])[:50]], s=1, color='green')\n", + "plt.scatter(bf_absolute[np.argsort(decay_ES[bf_relative.index])[-50:]], bf_relative[np.argsort(decay_ES[bf_relative.index])[-50:]], s=1, color='red')\n", + "print(spearmanr(bf_absolute,bf_relative))\n", + "plt.xlabel(r'Burst frequency $log_{10}(1/h)$')\n", + "plt.ylabel(r'Burst frequency $log_{10}(1/$(decay rate))')\n", + "plt.savefig('figures/Fig1e.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist(1/10**bf_absolute[1/10**bf_absolute < 30], bins=30)\n", + "plt.xlabel('Average time until burst (hours)')\n", + "plt.savefig('figures/Fig1f.pdf')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Figure 2b-c, ExtDataFig 3a-e, g.ipynb b/Figure 2b-c, ExtDataFig 3a-e, g.ipynb new file mode 100644 index 0000000..1917539 --- /dev/null +++ b/Figure 2b-c, ExtDataFig 3a-e, g.ipynb @@ -0,0 +1,887 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/site-packages/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.\n", + " from pandas.core import datetools\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from patsy import dmatrices\n", + "import statsmodels.api as sm\n", + "import matplotlib.patches as mpatches" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "ML_concat = pd.read_pickle('data/SS3_cast_UMIs_concat_ML.pkl')\n", + "ML_concat = ML_concat[ML_concat[1]][0]\n", + "\n", + "cast_bs_UMI = pd.Series([gene[2]/gene[1] for gene in ML_concat], index=ML_concat.index)\n", + "cast_bf_UMI = pd.Series([gene[0] for gene in ML_concat], index=ML_concat.index)\n", + "cast_me_UMI = pd.Series([gene[2]*(gene[0]/(gene[1]+gene[0])) for gene in ML_concat], index=ML_concat.index)\n", + "\n", + "gene_annotation = pd.read_csv('data/mouse_gene_annotation.csv', index_col=0)\n", + "gene_length = gene_annotation['txEnd'] - gene_annotation['txStart']\n", + "df = pd.DataFrame([np.log10(cast_bs_UMI), np.log10(gene_length), np.log10(cast_bf_UMI), np.log10(cast_me_UMI)], index=['bs','gl','bf', 'me']).T.dropna(how='any')\n", + "df.drop(gene_annotation['name2'][gene_annotation.chrom == 'chrX'].index.values, errors='ignore', inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def bin_array(arr, l = 30):\n", + " binned_arr = np.array([])\n", + " for i in range(np.int_(np.floor(len(arr)/l))-1):\n", + " binned_arr = np.append(binned_arr, np.median(arr[l*i:l*(i+1)]))\n", + " return binned_arr" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:5: FutureWarning: \n", + "Passing list-likes to .loc or [] with any missing label will raise\n", + "KeyError in the future, you can use .reindex() as an alternative.\n", + "\n", + "See the documentation here:\n", + "https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike\n", + " \"\"\"\n", + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:6: FutureWarning: \n", + "Passing list-likes to .loc or [] with any missing label will raise\n", + "KeyError in the future, you can use .reindex() as an alternative.\n", + "\n", + "See the documentation here:\n", + "https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike\n", + " \n" + ] + } + ], + "source": [ + "INR = pd.read_csv('data/mouse_INR.bed', sep='\\t', header=None)\n", + "TATA = pd.read_csv('data/mouse_TATA.bed', sep='\\t', header=None)\n", + "names_TATA = [gene[3][:-2] for i,gene in TATA.iterrows()]\n", + "names_INR = [gene[3][:-2] for i,gene in INR.iterrows()]\n", + "TATA_index = df.loc[names_TATA].dropna(how='all').index\n", + "INR_index = df.loc[names_INR].dropna(how='all').index\n", + "EPD_TATA = np.int_([name in TATA_index for name in df.index.values ])\n", + "EPD_INR = np.int_([name in INR_index for name in df.index.values ])\n", + "df['EPD_TATA'] = EPD_TATA\n", + "df['EPD_INR'] = EPD_INR\n", + "df['EPD_INR_and_TATA'] = EPD_TATA*EPD_INR" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "
OLS Regression Results
Dep. Variable: bs R-squared: 0.047
Model: OLS Adj. R-squared: 0.046
Method: Least Squares F-statistic: 57.30
Date: Wed, 19 Dec 2018 Prob (F-statistic): 1.87e-69
Time: 18:55:47 Log-Likelihood: -2909.9
No. Observations: 6935 AIC: 5834.
Df Residuals: 6928 BIC: 5882.
Df Model: 6
Covariance Type: nonrobust
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coef std err t P>|t| [0.025 0.975]
Intercept 0.8650 0.045 19.397 0.000 0.778 0.952
gl -0.0751 0.010 -7.354 0.000 -0.095 -0.055
EPD_INR 0.0180 0.079 0.226 0.821 -0.138 0.174
gl:EPD_INR 0.0003 0.018 0.014 0.989 -0.035 0.035
EPD_TATA 0.6018 0.130 4.617 0.000 0.346 0.857
gl:EPD_TATA -0.1006 0.031 -3.279 0.001 -0.161 -0.040
EPD_TATA:EPD_INR 0.1516 0.038 3.971 0.000 0.077 0.226
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Omnibus: 1012.607 Durbin-Watson: 1.901
Prob(Omnibus): 0.000 Jarque-Bera (JB): 1800.822
Skew: 0.948 Prob(JB): 0.00
Kurtosis: 4.625 Cond. No. 145.
" + ], + "text/plain": [ + "\n", + "\"\"\"\n", + " OLS Regression Results \n", + "==============================================================================\n", + "Dep. Variable: bs R-squared: 0.047\n", + "Model: OLS Adj. R-squared: 0.046\n", + "Method: Least Squares F-statistic: 57.30\n", + "Date: Wed, 19 Dec 2018 Prob (F-statistic): 1.87e-69\n", + "Time: 18:55:47 Log-Likelihood: -2909.9\n", + "No. Observations: 6935 AIC: 5834.\n", + "Df Residuals: 6928 BIC: 5882.\n", + "Df Model: 6 \n", + "Covariance Type: nonrobust \n", + "====================================================================================\n", + " coef std err t P>|t| [0.025 0.975]\n", + "------------------------------------------------------------------------------------\n", + "Intercept 0.8650 0.045 19.397 0.000 0.778 0.952\n", + "gl -0.0751 0.010 -7.354 0.000 -0.095 -0.055\n", + "EPD_INR 0.0180 0.079 0.226 0.821 -0.138 0.174\n", + "gl:EPD_INR 0.0003 0.018 0.014 0.989 -0.035 0.035\n", + "EPD_TATA 0.6018 0.130 4.617 0.000 0.346 0.857\n", + "gl:EPD_TATA -0.1006 0.031 -3.279 0.001 -0.161 -0.040\n", + "EPD_TATA:EPD_INR 0.1516 0.038 3.971 0.000 0.077 0.226\n", + "==============================================================================\n", + "Omnibus: 1012.607 Durbin-Watson: 1.901\n", + "Prob(Omnibus): 0.000 Jarque-Bera (JB): 1800.822\n", + "Skew: 0.948 Prob(JB): 0.00\n", + "Kurtosis: 4.625 Cond. No. 145.\n", + "==============================================================================\n", + "\n", + "Warnings:\n", + "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", + "\"\"\"" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = df.sort_values(['EPD_TATA','EPD_INR'])\n", + "y,X = dmatrices('bs ~ gl*EPD_INR+gl*EPD_TATA +EPD_TATA*EPD_INR', data = df, return_type='dataframe')\n", + "model = sm.OLS(y, X).fit()\n", + "model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "F test for gl = 0: \n", + "F test for EPD_TATA = 0: \n", + "F test for gl:EPD_TATA = 0: \n", + "F test for EPD_INR = 0: \n", + "F test for EPD_TATA:EPD_INR = 0: \n" + ] + } + ], + "source": [ + "print('F test for gl = 0: ' + str(model.f_test('gl = 0')))\n", + "print('F test for EPD_TATA = 0: ' + str(model.f_test('EPD_TATA = 0')))\n", + "print('F test for gl:EPD_TATA = 0: ' + str(model.f_test('gl:EPD_TATA = 0')))\n", + "print('F test for EPD_INR = 0: ' + str(model.f_test('EPD_INR = 0')))\n", + "print('F test for EPD_TATA:EPD_INR = 0: ' + str(model.f_test('EPD_TATA:EPD_INR = 0')))" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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NIjo6ms8//5yEhAS8vLzs+h7z8/P56aefuOmmm7jzzjtt1lkvk5KSwtGjR+nbty9jxoyx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Gk50T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\nkCsUCoVCkY9RglyhUCgUinzM/wOAM4RTY5+r/wAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "fig, ax = plt.subplots(figsize=(8,6))\n", + "red_patch = mpatches.Patch(color='red', label='Genes without TATA box and Inr')\n", + "green_patch = mpatches.Patch(color='green', label='Genes without TATA box but with Inr')\n", + "blue_patch = mpatches.Patch(color='blue', label='Genes with TATA box but without Inr')\n", + "yellow_patch = mpatches.Patch(color='yellow', label='Genes with TATA box and Inr')\n", + "ax.scatter(np.arange(len(df['gl'])), 10**np.array(model.fittedvalues), c = np.array(['r' if TATA == 0 and INI == 0 else 'b' if TATA == 1 and INI == 0 else 'green' if TATA == 0 and INI == 1 else 'y' for TATA, INI in zip(df['EPD_TATA'], df['EPD_INR'])]), s=1)#, alpha = 0.5)\n", + "plt.xlabel('Genes')\n", + "plt.ylabel('Predicted Burst Size from model')\n", + "legend = ax.legend(loc=\"best\", handles=[red_patch, green_patch, blue_patch, yellow_patch])\n", + "plt.savefig('figures/Fig2b.pdf', dpi=100)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df['group'] = ''\n", + "df.loc[df[df['EPD_INR_and_TATA'] == 1].index, 'group']= 'TATA and Inr'\n", + "df.loc[df[(df['EPD_TATA'] == 1)&(df['EPD_INR'] == 0)].index,'group'] = 'TATA and no Inr'\n", + "df.loc[df[(df['EPD_TATA'] == 0)&(df['EPD_INR'] == 1)].index,'group'] = 'Inr and no TATA'\n", + "df.loc[df[(df['EPD_TATA'] == 0)&(df['EPD_INR'] == 0)].index,'group'] = 'No Inr and no TATA'\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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oephNJcqB7vHczB46NQQGOTWsYlH1gjdtUvPpjeTAATV3Ho2qefNb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\nFRLlMrlKhWylAhdXkc5G/nADBBmXZjaJl03Ryrq8LeqLb+V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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df = df.sort_values(['gl','EPD_TATA','EPD_INR'])\n", + "df_pred = model.get_prediction().summary_frame()\n", + "fill_color_dict = {}\n", + "mean_color_dict = {}\n", + "g_fillcolors = ['r', 'green', 'b', 'y']\n", + "for g_name,c_fill in zip(df['group'].unique(), g_fillcolors):\n", + " fill_color_dict[g_name] = c_fill\n", + " mean_color_dict[g_name] = c_fill\n", + "fig, ax = plt.subplots(figsize=(8,6))\n", + "red_patch = mpatches.Patch(color='red', label='Genes without TATA box and Inr')\n", + "green_patch = mpatches.Patch(color='green', label='Genes without TATA box but with Inr')\n", + "blue_patch = mpatches.Patch(color='blue', label='Genes with TATA box but without Inr')\n", + "yellow_patch = mpatches.Patch(color='yellow', label='Genes with TATA box and Inr')\n", + "for g in df.join(df_pred).groupby('group'):\n", + " ax.plot(g[1]['gl'],10**g[1]['mean'], mean_color_dict[g[0]])\n", + " ax.fill_between(g[1]['gl'],10**g[1]['mean_ci_lower'],10**g[1]['mean_ci_upper'],alpha=0.5, facecolor = fill_color_dict[g[0]])\n", + "plt.xlabel('Gene length (log10)')\n", + "plt.ylabel('Burst Size (model)')\n", + "plt.savefig('figures/Fig2c.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "
OLS Regression Results
Dep. Variable: me R-squared: 0.014
Model: OLS Adj. R-squared: 0.013
Method: Least Squares F-statistic: 16.16
Date: Wed, 19 Dec 2018 Prob (F-statistic): 1.47e-18
Time: 18:55:51 Log-Likelihood: -6209.3
No. Observations: 6935 AIC: 1.243e+04
Df Residuals: 6928 BIC: 1.248e+04
Df Model: 6
Covariance Type: nonrobust
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coef std err t P>|t| [0.025 0.975]
Intercept 0.5024 0.072 7.000 0.000 0.362 0.643
gl -0.1072 0.016 -6.524 0.000 -0.139 -0.075
EPD_INR 0.0910 0.128 0.712 0.476 -0.159 0.342
gl:EPD_INR -0.0146 0.029 -0.506 0.613 -0.071 0.042
EPD_TATA 0.3674 0.210 1.752 0.080 -0.044 0.779
gl:EPD_TATA -0.0763 0.049 -1.544 0.123 -0.173 0.021
EPD_TATA:EPD_INR 0.0588 0.061 0.957 0.339 -0.062 0.179
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Omnibus: 66.899 Durbin-Watson: 1.967
Prob(Omnibus): 0.000 Jarque-Bera (JB): 71.809
Skew: -0.212 Prob(JB): 2.55e-16
Kurtosis: 3.263 Cond. No. 145.
" + ], + "text/plain": [ + "\n", + "\"\"\"\n", + " OLS Regression Results \n", + "==============================================================================\n", + "Dep. Variable: me R-squared: 0.014\n", + "Model: OLS Adj. R-squared: 0.013\n", + "Method: Least Squares F-statistic: 16.16\n", + "Date: Wed, 19 Dec 2018 Prob (F-statistic): 1.47e-18\n", + "Time: 18:55:51 Log-Likelihood: -6209.3\n", + "No. Observations: 6935 AIC: 1.243e+04\n", + "Df Residuals: 6928 BIC: 1.248e+04\n", + "Df Model: 6 \n", + "Covariance Type: nonrobust \n", + "====================================================================================\n", + " coef std err t P>|t| [0.025 0.975]\n", + "------------------------------------------------------------------------------------\n", + "Intercept 0.5024 0.072 7.000 0.000 0.362 0.643\n", + "gl -0.1072 0.016 -6.524 0.000 -0.139 -0.075\n", + "EPD_INR 0.0910 0.128 0.712 0.476 -0.159 0.342\n", + "gl:EPD_INR -0.0146 0.029 -0.506 0.613 -0.071 0.042\n", + "EPD_TATA 0.3674 0.210 1.752 0.080 -0.044 0.779\n", + "gl:EPD_TATA -0.0763 0.049 -1.544 0.123 -0.173 0.021\n", + "EPD_TATA:EPD_INR 0.0588 0.061 0.957 0.339 -0.062 0.179\n", + "==============================================================================\n", + "Omnibus: 66.899 Durbin-Watson: 1.967\n", + "Prob(Omnibus): 0.000 Jarque-Bera (JB): 71.809\n", + "Skew: -0.212 Prob(JB): 2.55e-16\n", + "Kurtosis: 3.263 Cond. No. 145.\n", + "==============================================================================\n", + "\n", + "Warnings:\n", + "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", + "\"\"\"" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = df.sort_values(['EPD_TATA','EPD_INR'])\n", + "y,X = dmatrices('me ~ gl*EPD_INR+gl*EPD_TATA +EPD_TATA*EPD_INR', data = df, return_type='dataframe')\n", + "model = sm.OLS(y, X).fit()\n", + "model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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wRoUreE7lxMKCRafQJ0IFh6OGdg3boWvjrlV2ib4yEZ8Vj6thV3E66LT2wjqw\ndCnw5pvAhg0sZayxkMtzzS6+gfmaNnPMnzVrWFCd06eZY6gBEJFus6batYGePQ3qk8N5lTA35aON\nDjYdELIgBE3rGNeLyMKCOfa0bw+IsM0URU7OE3h5dYSd3Wy8/voB4zRqBLiC5+jPqVNsqyE93SBj\nwZo1ayIlJQU2NjZ8aZTDMQGKuAY1S0dmMXM62nQ0SbtvvME+xsLSsjZq1GgGKyvz8pTgCp6jPzdv\nsiA2BnoCNG/eHDExMUgyt9C6gsDC/VpbA3XqVLQ0nHIkuyAbNSxroLqlnknCzZCaNWuWCRjEMQ5W\nVs0waFDJ5FQpKf8AINjYvFUxQoEr+KpBaCjLd9ikSfn226ABMxisWxf46iv15R4+ZIFuunRRebp6\n9epo06aNiYQ0gIcPmUvjuHHA+fMVLQ2nnPCK9UL//f0xvPVw3PjohsoyckEOzxhP9G/Wv0oNAjjG\nIzBwPIjkGDas4jwyuCWJqRAEYM8eZultStLSAHt7QEUgFJMjkwFSKfAy45lKBAHo1QsYMKDcxDIa\nPXowc9uX0c84rwYOdg5YMXQF1oxYo7bM/vv74XjIEb/d0y1jH6diIALu3BEXX8xYdOp0HJ07q8+w\nWB5wBW8qHj8G5s4FPv/ctP3UrcsyKMyebdp+VFGtGkun9DLjmUosLIAVK5hVS2Wka1d2jzmmxdsb\ncHBg6boqmBqWNSAdJsXAFgPVlhnSaghGtxuNkW1H6tVHZn4mYjNiVZ4rkBdgs8dmBCa+Ao7a5cSt\nWyzZjL6vYyLg22+BAzrYzzVuPAmNG7+nX4dGgkeyMxWKGXyfPkzJdepkeGAbIua82b49S+KiivBw\nIDqaZUWoSNLT2b41d2PjiOHAAeCTT4Dffzf9oNgM6LO3D3yf+yLxm0TYWpe0YbkRfgMj/xiJtzu+\njXNTzlWQhFWLlBT2eH3+OXORU/DwIXMEmjOHvabd3Njc7LPPgOL2vmlpwH/+A7RqxXKAVSS6RLJT\n5iaujJ/evXuT2XP1KhFA1L8/UUCAYW3FxLC22rdXX6ZLF1YmKsqwvgzh2TMmwwcfVJwMHNMzZQpR\nq1ZEWVmGtyUIRKGh7N9XgJ9u/EQjj4ykvMK8MucKZAW0494OCk4KrgDJTE9qbiolZCVUtBhERDR4\nMHtV+fqy7/b27HtkZNmyd+8SPXkirt3s7BCSy/ONJ2gxAPiQSB3JjeyMhUwGDBwItGkD/PVX0fGu\nXYHevYF794AlS4CLF/Xv47XXgH37gI4aXEd+/JENSV97Tf9+DKVuXSajGqM6ThUhOZl95EYwIpJI\ngA4dDG+nElAoL8Sq4ertVqpHQF5lAAAgAElEQVRbVsf8fvPLUaLypeeenojNiEXm95mwqmalvYIO\nHPM/hluRt7BzzE61xo+RkUCzZmyHcds2wMODmdsALCv348dsRj9gQMk8Wf37i5MhLe0W/PyGoWnT\nz2Bvv9vAKzIQsSMBc/yY1Qw+L4/I2pqoW7ey5woLiXbsIHr8uPzl4lQcubnst6+qCIL5Xt+dO0Q1\naxIdOFAh3T9KfEQx6TFljntGexKkoLXuaytAqoojIy9DuVrx+YXPafzx8SQX5Ebvp9eeXgQpKDw1\nXOX5O3fYDH30aKK1a1UvGCUlsTI9e+onQ25uNPn49KfERGf9GtACdJjBcyM7bSQmsvSu2rCyYj7T\nqqzmq1UD5s9n+/CmwNeXpZY9UbEWm5xi5OSwrILqbCXMhdxc4MkT/epKJOzZNkdkMpbNUczfrpHJ\nyM9Al9+7YPChwWXO1apWCw1qNkADq7JpgqsqOYU5sN1oi/772RT497G/4+yUsyYJB3xu8jl4zPZA\n6watVZ5v0YLN1u/fB374gb2yS9OoETNjunlTfL+FhamIidmBwsJU1KzZHL1734Wt7bt6XYMx4Qpe\nE8HBzLd8+nRx5WvVAqpXgE9saiqQkMByx3MqjvR05jN/4gRTfB07MoNIc2bGDCbnw4cVLYlxGTKE\nbR189lm5d12nRh183PNjzOszr8y5HnY9kLokFZ/3rfqGhABbIa5uUR0Odg5wsHMweX/N6jVDTmEO\n6v1SD2eDz5Y536IFS/Z57RrbLW3cWHU7zZsD9eqJ7/f58/14+nQhnj/fr6fkpsFMh99mgo0N0K2b\n+M2XiuK//2X553m0tYolPLzIxmLyZPYmMXfGjWOrVFUxwlkFhD32jvXGg/gH2Pf2PkgkEjx98RTf\nXf0OK4etRLcm3cpdHmOQkZ+BelY6aLuX3Ai/gVFHR+HA+AO4+8ldE0immuzCbGQWZCKzIFNtme7d\n2cdYNGkyA3J5Dpo0mWG8Ro0An8FrwtYW8PcvGaXt//4PGDNGcz0iYNMm4N9/TStfcaqKcpfLmR/L\nvLKzH7PHwQF48KByBcaZOZP5BtnYVLQkZsWtiFtosbUFXMNddar32YXP8NmFzxCSEgIAuB52HWeC\nz+DiEwOMa01ARFoEll5bisTsRI3lrjy9gvrr6mOL5xad+7CQWKC6RXVYWpSvq+x4+/Eo+LEA07uL\nXHk1AlZWdmjTZgWsrOyUx+TyPBQUVGz4ba7gdcXLiwXj0BQ/IC6ORUVYuLD85DIVSUnAsGGAk1P5\n9FdQALi6AhcuAFu26J+w+fJlYPt2zb+TKpydmSdEQIB+/To46La2xzFLojOiEZMRg+iMaJ3q7R63\nG7vG7oK9jT0A4ONeH+PqjKuY+PpENN/SHBtubzCFuDpz6MEhrL+zHqcfa07F2qh2IzSt0xQt6rfQ\nuY9hrYch78c8zOhe/rNafcIH5+cDu3ez/ffSREayeV5cnOq6T58uRnDwJyWOBQS8BQ+PxsjPf66z\nLEZDrDWeOX7K1Yo+NpZILmc+v5mZ2ss7OxPdv296uUyNl1f5+7QnJRH16MH6Ved5cOEC0c6d6tto\n2ZLVT0rSre/Vq1m9K1d0q8epcqTkpBitLf94f4IUBCnILcLNaO3qwsP4h/TPk3+IiF3bXp+9lJVv\nhBgGVQRnZ/anP3s2e83nF3NjX7uWndu2TXVdd3cbcnW1IA+PFpST84yIiMLCfiQfn74kkxn3HkMH\nK3oeyU4MV6+yZeNly4DVq03fn7kRFAS0bs2MCFXh5MQyro0fb7w+/f2Z4df06ar3Ups1Y8Pp1FSW\n9KY0Xl7M6HDiRN36JWJhrxo10k9uDkcNv3v/jqXXluL6h9fRt5mREpHrQOttrRGZHomkb5PQqDZ/\nvkuTlcXyw9eqxeyr27dnryGA2c+eOQNMmqR6N/TFi+sICBgHojz07n0fdev2NJmcukSy40Z2YmjR\ngiV0cTC9FahZosm9TyZjsfDr1jVuJgdtVjCnTwPx8aqVOwD066dfvxIJV+6vMGGpYXAKcMLC/gv1\nMizTxLy+8zCvb8XZlmx6cxNCU0JhU6vi7C3yZHk4G3wWYzqMQV0r88rxUKcO86qMi2O21e3aFZ2r\nX5+Zq6jDwqI6iPLQsOHbEIRck8sqFr4HL4bXX2dDukmTKloS/TlwAPj5Z+O3W60a4OIC/P238dtW\nsGQJU/bFBxADBjCDR455Ex0NnD2ruy1EBbHFcwt+dP0R50NMkx44Iz8Dl59chlzQLfpfYnYi1rqv\n1WoUp4lJnSfhB8cfIJFIQESIzYhFgaxA7/b04dCDQ5h8ejK23t1arv2K5dEjNm+4d0+crWxhYQri\n4vahbt3e6Nr1HF68OI+AACOuZBoIV/CvCj/8wDK65eQYv+0JE5irnql48AAIDASys03XB8c0fPIJ\nG4jdu1fRkoji+8HfY/tb2zGxk45bOyL56cZPGHN8DE4HaTZuK80RvyNYdmMZjvgdMYocf/r/ieZb\nm8NqjRXW3V6nsaxMkOHB8wcwxnbuePvx+LTXp5jSdYrBbenCxdCLWOu+Vus1WFkxG+r588W9KsPC\nliE09FMkJPyJmjXbAKiGRo1M8+zohdjNenP8mFWoWnPH35/o9u2KlkI/CgqIUlO1lxMEorNniZ4+\nVX0+O5slNOGUH66uRF98QZSTo7mcXM5+t0qQbEYQBPJ77kcFsgKd63rHetNU56n0PPO5TvWSs5Np\nq+dWgw3/otOjSRAE8ojyoBZbWlCdNXVot/dujXXW315PkIIOPzisV59PUp7Qnw//NEloWrF03N6R\nIIXK8MGl+d//mEGdp6f2dt3c6pKrKyg3N84IUooDOhjZVbiSNuRT6RV8vo7ZhgIDiTIyTCNLeVBQ\nYFr5AwPZIz1ggOrz77zDzj94YJr+c3OJzp9n/5YnT54QbdqkXYmaM5s2sd/GyamiJdHKqUenCFLQ\nsuvLjN72i5wX1HdvX9riscXobR/zP0aQgnZ6afA+UYFntCcNOjCIAhMC9ep35JGRBCnobvRdveob\nA/94fzobfFZU2dhY9mcsZqwZFbWFwsOlBkqnG7ooeL5EXxpBYBsxpZdyHjxgqYdkMuP04+nJ1oM6\ndGBhZrXh788y002dqn+fK1cCn35acfuhw4ez+OxpaaZpv2NHYOlS9bYGb78NODoyo0lTsHs36+P3\n303TvjpWrQK++aZ8AysZm969mWXT669XtCRacbBzwKAWg/DftmW3pTLzM5GSk6J328k5yfCO84Zr\nhG4BdsTQvmF7dGjYAZ0a6ZYTY0DzAbgz+w66NNYvO+TPw3/G8iHL0bOp6SzLtdGtSTeMtxe3N/7a\nayzAo5hAiC1aLEbr1isMlM6EiB0JmOPHJDP4zZvZTOJwqeWo4cPZ8btGGoX6+RHVqMHavHlTe/m0\nNKI33yT64w/9+3ztNdafITO9nBzxSZFLM3cu82+vzDNNTYSGshzp5b0N8PQp0dat5b9yUAUJTAik\n7IJsIiKKSoui3+7+RjkF4p/Xjts7UvVV1XWqo2DG3zOoy84u9DTlqco88RwOEZ/BG8aAAUCfPkDP\nUqPN334Ddu1i5xQEBQGLFrGc2LrSowfz4b5/Hxg6VHv5+vWBK1dYchB98fICQkPV+7OL4cMP2aqD\nPnHWd+1i9QzpXxXbt7PfS1VqKGOjKbJehw7M9La885q3awd8+SVQs6Zp2n/wABg7lj07Yrl3D/jp\nJxYerJJwN+Yuuu7qijnn5gAAVrutxqJ/FuFcyDnRbQxtORQDmg9ANQvdPZDDUsPwLPUZGls3Nnqe\ndE2k5aUhMi2y3PozFml5aTgecBx5sjxR5ePigH37TP9IymSZePRoCpKTzSA8sdiRgDl+KnwPfvFi\nNiM+epR9FwRxkdOePyc6cYJIJjOsf0EgunWLKMV4EbdKMGoUUadOJXN+HzxI9MYbukeIMyXvv89+\nh0ePTNvPX3+xfs6K28sTjSCY7jc0BoowXnv3iq+jsFRydzedXEYmMSuRhh0eRn8F/kVERCFJITTb\nZTYlZiWKbmPSyUkEKajaqmp07dk1+u+R/5JPrA8RMQM3TYZmMrmMcguNtwoTlRZFTTY2oRWuKzSW\n67m7J0EKna7THFh2fRlBCtrnu09U+c8+Y4/kyZOG9fvrr0QNGjCTn+LI5XkUFraC4uL2k6sryN//\nbcM6UgP4DL6cWLYM+PNP4P332fcdO1iCmjNnNNf75huWbezKlZLH09KKZsbR0aqDIhfn9Gk2+581\nSz/5r11js01vb9XnX7xgs+Lie/azZgG3b5tXMJg//2TD886dDW/Lx4etzKiiRg22+lCjhuH9FGf5\ncpbsxc1N9XkPDxZroKL4+mvg1i1g9mzxdX7/HTh2DBg0yHRyGRlba1u4fuSK/7b9L+SCHB4xHjjo\ndxA7vXeKbsOxlSNsa9vCuro17j+/j2vh13At7BrOhZxDi60tNLqkWVpYYoXrCvTa0wtZBVkGX0+e\nLA+J2YlIyFJt45NTmIPQlFC80+kdjGk/BvVr1sfZ4LO4G1My81tqbir+ffYvqBxsdzLyM2CzwQbv\nntSeS/3DHh9iQb8FGNdxnKi2Fy8GfvwR+N//2Hci/VJd3LvHXtUXLpQ8npnpi8jIlUhMPAkHBze8\n/voh3Rs3NmJHAub4qfAZfGkuXiRq1Yro3j3N5Xx8mOtQenrJ44pZj78/kbU1+6jjwQNWtkUL1q8+\n/PYba+PECdXn5XLDVxnKg3v3mPV1WBhRdLT+7eTmsvthY0MUGWk8+Ypz9CjRvHklV0WOHmXPjbq4\n+02bMrlKPy8coxOaHEqQgiafmkzhqeE08cREuh+nX04JmVxGd6LuUIGsgPzj/cl+uz1dCLlQoowg\nCPQo8ZHS5W744eEEKXR2o1NHXmEeCWrMwd89+S5BCvKK8SIiorTcNIIUZL3GmsJTw5XlPvz7Q4IU\ndPnJZaPIpIn0vHRquL4hvXPiHZP2s3IlW5y0ttZ9MfLyZWY+5exMlJcXQ4mJLvT06fckk+XQ8+d/\nUHa2njZKIgF3k6ukHDtG9PbbzJVswQL2UUdSEtGgQWzJXB/u32fLwjHa/UKVCAIz9lNFYiLRnTv6\nySIWDw+iDz8su5zdvj17lC0tiRo10r99QSD68UeiunVZWwW6+zlrpWtXJqsuA5ELF4h27TK+LJwy\nJGQlkP12e1rjtoaIiBZeWkgtt7Y0auKZ4pwLPkeQgr7991siIsqX5evU14WQC+Qb56tX34cfHKZe\nu3sRpKAlV5cQUdEAo7gLoFuEG009PZWSs5MpJDmE5l2YR3EZ5ef3rY3U3FS1gxh1WFsTSSREtrb6\n744JgkC3btUkV9dq5OoKev78KD15spgKCl7o16BIuII3hMREpljVzab0YcsWorfeqjjr8fDwkopZ\n4S8+cqRu7Sj2Yq9dK3tu5Eh27sKFsueMxcyZrI/z50sev36daPt25udub2/47Pvrr1lfS5cS/ec/\nxp3NR0SYfiBkbmRlscFrlhGzavn7l4sdyDsn3yHLlZZ6KbQXOS8oX6Y51sXTlKfUf19/uvJU9+yF\nydnJBCmo5daWOtdVEJocSjbrbWjj7Y1EROR4wJEgBV17xv7Gj/odJZv1NuQd601ERfvee310sMcw\nITfCbhCkoFU3V+lULzi46BXv4UHUujXR1au69x8UNJsePZpOYWErlIo+IeGU7g3pAFfwhnDkCLst\n33zDoqetWUMUFSWuriCw8gqju2XLiDZuJBo4kLUZFcWGi0uXMtem7Gz2pOnCwYNEXbqIlyk+nvVd\n/F5lZhJNnEj055+69e3kRNSsGdHDh+y7v39R4BpnZ6Jatdiw2FTuWi9esAGEXI2h0g8/sGsdO5bo\n9GmmTI8dU19eGwsWEFWrRvTsmf4yc4qC2GzaZJz2wsNZe/37G6c9DQiCoJfLWmJWIkmkEhpyaIgJ\npGIIgkCb7mwilyAXo7UZ9iKMnB85K2fEmz02E6SgG2E3iIgt4zsFOBnVGNAQAhICqPmW5nTs4TG9\n23ByYo/Tbs0B/ZQ4OxONGcNeRwpSUq6QqysoOPgTkstNsPJXDK7gDSEvjymFlBSiffvYLfruO/Xl\n588nev11pugyM1n5Jk3YHitAVL8+mz0rwqceOlQ0gJg4kf3fz0+8fApTUHX7/FFRRP/+W/J63nqL\nWfyHh4vrIzCQDUzyNLzYFDYAbxezFP3pJ5ZMWexymUxGdOkSu2/GIDubDa4Aos6dicaNI9FxBtSh\n7+CAU0REBLM7iIgwrJ3ISLYKlptLNGmSblb9CnJyypo/m4Cs/CzqtacXfXPlG73qJ2UlUZ+9fWjS\nyUlGkSckKYS+ufINJWcn61xXocwz8zPpiN8RysirxNE01ZCYKP619e67pDIkilxeqLqCkeEK3lhk\nZDCfiOcaDF5GjWL7tYkvXUxcXYsUdosW7FzxGW1ODhs4JCYyZT90qG6bQIWFLJaiOgYNYj9r8ZdY\nYSGbWdvYiOtDMfAoPlAoTWoq0ejRmlcB5HLW1uLFbAWhfXt2LDyc/TUdO8b6+frrojpffEHUoUPJ\n4bGu/PsvUUgIGwR9/z0PAKML2dnM+NIQY0VTEBJCytUZQ/joIzIX973t97ZTy60tKexFmPJYgayA\ndtzbQZCCLFZaUKstraj/vv70u9fv1HxLc6VBnDaSspPowXMWkjkkOYRe2/QaQQqtcec1oZjNr7+9\nXu82KpITJ9iiT+nXZ0EB2+UTu4OakUHkq5/Zg1HgCr48kcnY3qIglLSMJiL6/HO2lqPLLFDTMPLS\nJaJ+/TQvGZ8/z1YVise5FwSiRYuIVqwQJ0NoKHuR1q9vWFS2nBw2wGnThqhnT6K2bYuU+pYt7C9t\nypSivxaZjKhhQ3Z+82b9+zWE+/eJrKyYfOWJlxcz7tsnzqfXZCh+n3nzKlaO0qSmsq2uX38tOhYd\nTeTioluCGmdnoiFDNA/ay4lFlxcRpChhJNd5Z2eyXGlJkIKmOk+l7ru6E6Sg/vv6E6QQHU990IFB\nBCnowfMHBCmoxqoaVO+XevQiR/+Bc3R6NH1x+QuKTDORh4mJyMzPJP94f5o9mz3axXNupaSwVxTA\nXkWVAa7g9SExkahdO7Zvrg9jx7I9aMXMUxDYfrkuBlXLlhFVr04UFKT6/Ndfs59MX7c4XfjuOyIL\nCxY8Zvp0tqWg4IMPiOzsmNvW2bPMvU+dwVNsbMkVivv32fL59evs+7Nn7LuTE9Hff7Pr69iRKK6C\nrHR9fdlvYKz9YrG4u7Nr37atfPstTUYGM6asDHYHb75JotN+lTNbPbfSgfsHShw7G3yWbDfYknsk\nWz0QBIHSckt6pYx3Gk8OvztQ552dacD+ARQQH0AzXWZSSnaKTsr5wP0D9N5f71F2QTa999d7BCnI\n6mcrvZboKzsTnCawZDcR98vMV168YON5S0uiU3raxuXnx1NhoRrvIhPAFbw+KAx33ntPv/rTpzPF\n0KQJUffuRUuK9vbi21ixgvlvhISoPl9QYFzrfm3IZGwf3tKSxbFXMH48Ub16zLZg6lR2nW5u+vVx\n8yarv3gxGyTMnk3k7a1bGxER4tLJmiPFV3cUMQemTGFbN3z/XzOurmzJvV8/5pysCZlM89ZWMVJy\nUuhk4Em90sESERXKCwlSUP1f6pc4vtd3r6hZuCAIZLvBlppsbEJERNs8t9HPt37WSxYF/fb2I0hB\nHlEeGsu5hrtS/339KThJR+NfI6Or25smjvsfpzf/eJMuXUun9u2Nuzsjk+WQq6sleXq2M16jWuAK\nXl8yM/V/qQoCC0hSsyZTiMnJbLm1+NNUWMhmxMbMeS2XE61fr5+PhxjCw5nlenx8yeOKa8jMZIF7\nDCE6Wv+AOomJ7DG2tmb+LqU5eZLZSZhDKNioKOZ5oCAggD0ry5ez+3n5MpOzQwei2rVN44df1bh4\nkcrYcahi3jxWTtUzUooFFxcQpCCnAP1T17pFuCldy4qjSGSjYIrzFJrgNKGMQqv3Sz2CFJQvy1f+\nXybXP+hUZn6mKH95qauUIAWdDDQwnquOTHGeQk03NaX0vHSa6jyVaq+pTQlZCUbt48AB9gjoGzpE\nFYIgp4cPx1Fo6ELlsezsJxQbe4A8PdtRZqYOBtQi4QreVOTlMVes4kuCqalsaX/hQqbAc3NLWoVn\nZrK95xEjity4duxgdY4f112GrCxmtT9nDntZXbjA2uzSRXX569eZj7oqtzovL7Zfry54DRGTE2AD\nFmNw8CC7V5oGUt98w1YIxFhd5+ezDHUA0c8qZjkKk1cvccZJJqVtWyaLYrXh8WO27752LVPuANGM\nGcx2IaPqWSqbjEePtA+GjhxhW0EinqnzIeep1upaJWK4p+Sk0MgjI+m4vx5/sxqw22RHddbWKROj\n/mLoRToRwCJMBiQEKOPZm5pCeSEFJASonUEnZSfRrYhbRu/37eNvU521dSg1N5U+PvsxNVrfiJKy\njRPnIF+WTwWyAhIEFtdL2/wqLo49JqrKLVnC5nBrWBwkysuLo+DgOZSVxfJgyOWF5OpqQbdu1SZX\nV1BS0vmyjRiISRU8AGsAlrrWM8WnXBT83r1M2fj6MusMgCVbURAfz2Zh48YxZXP6dMmXc1ISqwMQ\n7dzJlhP//JN9X7pUfb9yuWqzzhcvWJzEoUNZGw0asM0jhW96aRYtIpXBYYjYtoK2Pf3du9kgwFjL\nxR06sD41LZcuWsSuMSxMfZmCArb/n5HB/hK9vVmb48eXtP7PzFR/b8Tg4cGi450+rX8bCrZsYQMz\nVfcyJYUpdzOw7jYrIiPZMrw6uxQjIwgCnQg8QZCCvr5StCrgE+tDkILePfmuUftLy00zyPBNLE9T\nntKpR6cMXvp+68+3CFKQd6w3BSQEkN9zNkNNyEqgLR5b9L4WQRA0JuLRF0EQqPHGxtRmWxvRdRo1\nYq+o7t3LnlNEEx8+nH2PiztArq4gL69elJ8fT4IgUEjIPHr6dBnl5ZnGkNOoCh6ABYCpAC4CSAQQ\n/fLfxwA2AmgvtjMRfR182XagmPIm84N//32iPXvY9zFj2G2SStmLuUEDKpNTPSeHnVOsAX3/PTue\nn89mlXv3Mr/y4svQ9+6xmXxkJKuXl8cU1cmTLPjNW2+xICuJKjI85eSwttavL5JTHbm5TPmp+sNO\nSGCDA4VcgmC6GOwKwsKIVq1i9+nMGfXltL2IDh4sO0i6epUd++gj9n3tWqJu3cQvz//zDwvkU9ww\nUrEEzEPFVgy7drH7v0q3SGX6cin0EkEKGv3HaOq8o3OJvejAhECKTI0klyAXg5bLxVIoLyyjML+6\n8hVNPDFRrTL86cZP1GVnlzL1HA86lrHY14fzwedpqvNUyszPJOs11mS50pIEQaBVN1cRpKBf7/6q\nvREVnAs+R7cjb2svqCOCIFD/vf3J8aCj6DpffcXmdMXVy7NnRE+esFdlQEDR6z8zM5BcXUGurqDY\nWC3vYiNhbAV/C8BPALoDsCh2vCGAdwGcBjBdbIda+hoCoFeFKvjISHZb+vZl32/cYEpCMQtcv54t\nMatSQLGxRLNmFfmgu7mxtv73P/ZdEJibz6VLzBIdYIocYIr9+nX2/wEDmItd+/blk2Bk6VLmr75u\nHevf2Vl7naNH9Qs0QkR07hxbmr6ie3hOImKZIhQ+0cX3tAWBrbIoVlD+7/9YOUWQoe++I5owQf1+\n/549rHxpc9rsbNXlTc2NGyw2/qu8F5+Xx7wrjBnmVgPR6dE0/PBwmnxqMkEK+ufJPyXOz3aZTZCC\n/n78t9a2fGJ9yHaDLf35UHWsCEEQKDw1nARBUGnQp7D+jkiNUB5rs60NWay0oJwCpmEiUiNo7LGx\n5BntScnZyVT/l/oEKcq4st0Mv0k/XPtBY+hcuSCna8+uUWa+uMBTG25vUIaIfZ75nH5x/0UvK/3s\ngmyCFGS7wVbnumLosrMLVVtVjbLy9XuGcnNZGBGJpOxrPzc3glxdQW5u9UkmK59Q5MZW8NWNUUa0\nQEDrClXwRExpqJo5E7FZ+fnz4l76MhmbaSp8MxQGYa1bs/3XX35hbmNLl7J9cHt7dt7WtmgWagr+\n+acoHRIRWzaXSNiSd6dO4iLrWVszWSsi29zmzWyIffUqc6lTN9AoKCjpvqe4Tk2R8wwJsEPEBnXF\nBx2GoAhxbMgWgyZSU4kmTy5poCmTcet9Ysru78d/U2xGya2kezH3yHqNNTXb3ExrG9fDrhOkoE0e\nql0u9/owq/ovLn9BkIIOPiiy/krNTaUZf8+gzjs6l0g+k5KTUkImpwAnZbKYoKQgghT09nH98pD/\nFfiXUp7yZo/PHtE+/roy9/xcGnpoKBWqiDQ3aBCbT2kiJ4ftu7doofp8bm5kGTc5mSyHnjz5mtLS\njJ93olIb2ZmFgteEYpY3YACbyevK33+zGIeqlsK3bmUbPwBR8+ZsuOjhYfwZ5KVLzMf95EtL2efP\n2UBj5kzV7m5797JANcWDg7i7q046oytJSSzwiD5OqN7e7F7Nnau5XFgYC+CSnKxb9jxdUYQqbtqU\nbb8cOWJYe6GhbBBmTK+L4ri6Mnnff599l8mY7F27li0rk7EtFXPwRtBEQoK4kGReXhqDOCnSxvbf\nVzbe/eADg2nwgcFq6yZnJ9Pgg4Pp0INDZazmi3Mn6g512tGJdtzbQfV+qUfOj4pWzt4+/raoFK1y\nQU5uEW7KcLKxGbElZumCINCMv2fQl5e/1NiOou47J98hz2jTxBXILsimHfd2UEy6/n+DwUnBFJUm\nMg+HCFq3JmpZLFdPejrz1L1xo2Q5QdDtzzA11Y1cXUEPHxoYeVEFpjaymwrgBIBjAI4DmKJrG1ra\n16jgAXwKwAeAT8viv4ypkcmYoV1YGPNTrlWLffThp5/Yrb90qey5uDgW8CY6umj/97PPDJNdFcWf\n1vbtierUYX198EHZsjNmsHP377OXZ5cuRB9/LL6fFSvKLvvL5Wxj6/PPWdtDh2pup7CQLa//+CNT\n1Ar5ExKKVhHc3Yn++E+5susAACAASURBVKNsXYVljKkN2ASB7RXv38/6q1mTrfjcuyfu7ZCSwjwI\nShuUvfUWG1AaW9ELAnuTKVYt5HKm3Pv1KzuoPHOGXdOcOcaVQR3HjzM5dAl4lJDAZBw0SHO59HRW\nTt2UjJjl9fTT06nttrbUcF1D+sX9F9FiKKLHTTo5iU49OqXV97w0gQmBBCmoycYmKpe8g5OCtSbA\nmeo8lVptbUUvcl5QtVXVyG6TnU4ymII/H/5JkILmX5yvV/2cghyCFNR0U1MiIprsPJmabW5mUGx8\nmazkIuS1a+zRqFNHc73bt9m8R92fpCDIKSHhL8rNNd5gRIGpFfyeUt936tqGlvbNcwa/fTuVMLaK\njNTfIO3sWeayo80yOC6OvdwVUd+MiSCw1YJevZgh4cCBzOWu+JK2qyuLl19QUORml5rKlvcdRRqt\nPH/O7lv79iWPK/bRv/uOzRq1RSNLSyt6KQPMFqI0Cje00mFI795lLorlFZNeoUBsbYtcI0+c0F5P\n4V1Rvz7R4cNFxzt0YCF8y2M75NkzJsOoUSWPp6Qw5a5rECJ9UaQG1iVKXU4OU+7aolEKAhtIaTGc\njEiNIEhBkIJmnplZ5vyn5z+lumvrqkwlG5ocSjHpMQQpqPmW5srjMrmMRh8dTXPPs1WnqLQoSs8r\naWeTmZ9J453G09GHR8u0eyviFkEKmvH3DHrzjzfpZIBqf/U3j75J1musKS03jaLToyk+M15lufIk\nPS+dfr71Mz17oVuUxGcvnlFWfhYJgkBzz89VBv0Zc2wM1Vlbp0w0QEOQy9mf28CBmst16sQeT7H5\nu4yJqRX8YQBjXxrdjQFwUNc2tLRvngre15do8GDdMr9VNF99xfbKVfn+CgJbn5JI2EtRVR73Vq3Y\nI1LaHiE7u2zcfU1cucJ8lYvzzz/MeLH0cQVnzpSNThYZySLftWzJtjpKc/Mm80gw1ZK2Lri6sr14\nd3cWA0Fd6NegIJZzXpG9b9kyKhO4paBAc2Y/Y+HlxVwMBw8u/1j8xZkwgcV6KM+ojWqISY+h+Mx4\nlVbrn57/lOqsrUOPEx/TosuL6GF8WVuJ3d67Sxjq5RTkUPVV1anDbx0oISuBIAX13iP+PRaTHkMD\n9g2gdbfXaXTbEwShzJ5zRGoENdvcTG2ymJScFDrid0RrKlhjRpnTxNOUp8rVjNFHR6uUwxjeDAkJ\nuqfc8PRk5lXqbkVy8mUKDJxEBQXGj7BpagVfG8B0AEtf/ltL1zY0tO0E4DmAQgAxAD7WVL5cFfzt\n2+ylrQ/79ukf6NgQvvySbSOoG2ZmZTElrkjwUlrZ3rrFLOsdHJhCJmLK5urVomQ2+eqtckvg4yP+\nHshkTJ7atdWXuXyZLb2XjrBnbhw5wpLtqAs/7OfHrrX4rDMx0XiGbnl56vsujcJwUtG3m5vqgZ86\nCgvZdoQ62Y8fZ5FCtF1b375sFaP4oObmTfEKPz+/XAMFOT9yJkhBn577VFT5pOwkysjLoLzCPBr1\nxyhaeXOlXv0+jH8o2uL9x+s/0nf/fkeQguZdUJ1ISHG+dAz94ow4PIJqra5FpwJP0U6vnaKUfVRa\nFG2/t12nHPJuEW4EKWiWyywaemgo7bi3Q3RdXenYkUrEn9IHmSyLPD3b0+PHbKUnMHASubqCUlP1\nDOGtgXI1sgOwxNA29P2Uq4KvXbvky08Ve/awF1jxhz4/n5TLrsZAjMvUuXOaX+p797IY8grlfPky\nmzGqatvFhcm/fDn7rtiq2Ly5KEHKhg3aZWrfnrQGuCnOX3+x61DHrFmsPVWGfnI5G7zk5DD7AW1B\naqKi2DVoUgpxcdoVk6sr23c/WmxpdckSUrv/n5LCksskGCkkpyAw+4jifxcffsj6FxPKePfukslu\nFAM/MVsb9++zmbdiG2vcuLLZCxXPgLZBmUxW8llMSWH1WrXSLgcR27uvXt2oLqaF8kLyj/dXqdAK\nZAV03P84JWap8bwpxu3I29RmWxtyDXclQRDIKcCpRLpYQ4hKi6IFlxaUcKsjYvYEkIIarm9I2QXZ\napVyaHIoLf5nsdrrCE4KJkhBlistqdXWVgQpVG5PlGbOuTk6h7+NTo+mPnv7qN2CMCa//MLMqgzZ\nASsoSKWbN63owYORyu+pqW4mWe0w9Qz+r2KfUwCe6NqGsT7lquAPH9Ye7KR5c3ZLS79YLl3SLRnL\n8uVsWFnaPcrJiVTuP3t4FMXYDg1lZXr2VN9+r16sjKrwtaoIDS16+oOD2Yvc359o2DC2H79/v/Y2\n/v2XeQmIeeDPnWMKXhNZWeqN16ZNI6URI8Dk1MRXX7Fyhw6plx1gxpGauHaNbXkUb0cQ1If53bBB\n/ABJDILAVgs6dy46pljynzRJ9/ZOn2arTz4+zJ1O0+DM0ZH107s3CxQElLXGDwlhM3FdEQR27/9U\n7U9ehjlzmBxG3NYwJEZ7QEIA3Y2+S4Ig0BG/I8pZskeUB0EKGnF4hFajOXXIBblyZrzVc6vafO33\n4+7T40TDtjxkchktu76M/nnyD92LuacMpauNJylPaPWt1aJXG8yB/HwW2EYdPj5sYVPx2o2O/o3c\n3e0oLe2uyWUztYLfX+r7Ll3bMNbHLPLBFyckhBl0aSIxkb04VQ0X8/NZqFWAfX74oeicXM5c24CS\nft9eXiziXbVq7PuRI2yP+mSxF9EffxCNHl0Ucz4+vigHu77Mn89kadjQsHZUoVgt0XdI/dNPzL4g\nPp7NnDXNGO/fZwp50yb1M/jHj5nljZgtBl1G7AkJRKtX6zeDj4sjWrCgKIhP8f6Ly5CUxAL+6JKM\nKDGRqH9/Zs9AVDQActKQfMXPjw2AFasckZHlm+FvyRLmAWJkQ8qnKU8pX5ZPN8Nv0oD9A/TKsmaz\n3oYgBfXc3ZOabW5GsemxJAgC5RXm0ZKrS8h6jTW1+1W/bGSD9g8iiVRCD58/pKz8LDr68KhBVuXG\nRhAEjTHlFbYNQUlB9PHZj0W70KXkpKi0eTAWH3/MHnl12b4VgTR3vNw5ePLkK3J1Bd28aUWCCULu\nFsfUCr5Nqe8NdW3DWB+TK/iRI9lsVy5nQ7Xt2w3fG1XEf1e1txkXx87Z2bF/3y4VsOKbb4qWyonY\nC1ShZH//nR2bNIkdK67Au3alEhHqvv6axc8PDmaDir/+Up1wRtP++qpVzKLd0IGCKi5f1hzGVhvJ\nyWxwIGYv+z//IbXmsM+eMQ8DRaKa2FjmvmgqfHzKzpLnz2fBsUsPAn7/ncktlapuKyhIfbAmbTx4\nwNp+913mFpqRwX6TighqJBZb26KB8ebN7FhoqPo3tAjuRN0hSEGfnP1EdB3/eP8yCnaX9y5adWsV\nvXHgDerwW4cShmGCINDgg4NpvNN4vWRstKGR1n1zVSRlJ9G54HMmif9eHMWqgkuQCwmCQAsvLSSp\nK3tmfWJ9SCKV0Dr3dbT8xnKCFLTXR1x0TEXo3dBkHa3jRHLiBNvpUbVo9eOP7BMcXPR6SUm5Svfu\ndaPAwEnKZXm5vJCysoKMvkxfqQPd6PIxuYLv1Im9XGUytuQNqHZti4wk+vRT9ZbSxfHyYr7f6jK4\nhYSwWdfJk9qX0AWB5VHfvbvoWHZ2WRkVYXEVL7vly5lNwNOnRUPRJUtK1jl7lh0vnqXuzh2ib79l\nFtYAm+WJISqKKdLvvmPf//qL7c9qevADAphy+eQTtoQdGcn2dbWl+wwMJKWbF8AGRaUJCWGbbk+e\nsOXs0tsVPj5sZq3ILaAYVDVowPbYxfzByuVsz3nAAHF2EzExrK/SGS4+/JDIyqrsmyYnh+31q3qO\nFP7gqgLWiCUsrCh+QLARcoNLpUW/vyoKC3U3ZS7O2LFM1mrVilwMFV4gekYnjEmPob57+5KTv7i0\nsQr/9/HHdVPWgiDQxdCLovazS1NrdS2y+tlKtDW5otz0v6cTpKBLoSpicejBwksLyX67fRmXv4uh\nF6nV1lbkGe1Jx/2Pk0QqoUYbGhERkd9zP7JeY03bPLdRRl4GOT9yVrlV8TTlKT1JKblefuD+AZp4\nYqLGQELa+PffItthVcjl7NX5448lj1tZsddAcby9+5CrKygr6zHl5ydScPAcCg7+jFxdQYmJ2sMa\n64JJFDyAr1R8PgbgILYNY39MruBlsiJ3MF9f9S5Y27axW7luXdlzhw6xl3Tp2XBqKssuZ2hoVDEo\nrKMzM5lydnEpOvf8ORuclLagV+wnFw8GonjhKwL1fP65uP7DwpjR07yX1rsKf3V1S9OKiHDNmrF/\nW7dmAx51Crs4sbFsHxpgHgSqoslt3szOb93KBgTt2pUMkKO4zlu3WAS8Ro1YnQULxAd6+fdf5t/f\nuDG7j+rcARUUFDDDwdL2DILAnsO8PPVJg1S19cEHRTPZ0oSHM9mK23JcusTC/166xJ6P6Gj2fDo6\nlhxEXLnCBoOaBi0rVrDohMUjytWrx1aN1K2ofP89qV3ZImKrCIq/RUFgv0vxAUFWFsvzsGABW8VS\nJH/69lvx2yabNqkOlCSS1NxUGn10tDL2vEuQC+3x2UMD9w+kd06+o7aeIgDMmGNjypyLz4yn9r+1\npzVua1TWDU8Np/DUcFHyfX3la7JYaUFBSUHkEeVBH5/9mFJzxW+j+Mf7q1Woo4+OJsuVlmpzuJ8I\nYBn6pjlPEy2vgtqra5PVz1Zayy2/sZys11hTSLI4r5EaNdifplzOXtNTprDPmDFsp1UREqJt25L1\ngoKKxry5uZHk6dmBfHwGUUTEehIEgeLjncjVFeTv/3/k7d2bsrONMEAuhqkU/HEAoQA2v/yEvDSy\n8wbwndh2jPkptz14ba5g2dn/z953R1dVbV/v0LsgTbAhWBBBBFEReaKiz6dgQ8GnPhVFRWliBRte\nQu+h995774QEEgIEQgipENJ7IaTd5NYzvz8m+5xzWwok743xjd8a44zk3nv62WevNtdcjOm44ziX\n4XHpVRQW0tv46CPPRkF5Utne7PXq8Viyde19t4g3LBYClzzlqC0Wx7BsYiIVrd1eFoWT+8lfP7FH\nRpadE1YUGg8zZnDdlBRuf+pUxWhIi4roCf/4o/vfS0vZT8Bk0loAf6/j3752jZENm00rYyvL+3SW\nqChu07MnIwHNm1csulOWjB7Nfe6tAr7u9eu5r+E6RrFt2/jdhAn8Kxsk6SUjgyVs7koq9SI59PWE\nQ9eulU3sdOgQ02HuvPisLOJP+hKhrFIUd+7sOg4ffJCGRGVz8aWl3Gfz5m5/3hC2AfPOzavULu+e\ndjeEQaDR5EZ4bP5jbtcpMBWo6/jGuxJaScrcT3Z+4vD9uZRzaO/THsfjPL9H13Kv4ej1o4jIioDF\nZoHB34BmU5vh+o3rHrfxJIFJgRAGgf/s/A8SbybC56yP2vAGYGSgrGYuOcYcDN0/FBfTLmJ5yHKX\nZjhlyZjjY/DrsfLfv99P/I7a3rURnVOx1sJbttBOvH4danZHEnrK1zchoexMV0HBBbWbXETEQFit\nRTh3riMuX369WmrggepT8KeFEI10nxvd6jRXXwgRVdH9VOVS7Qo+IkILb0+YcHv7WLNGmzCPHGHo\nWSK7//qr4mVjzvuTnoaiuIKZwsI4US1bRrT7/PnMv3/4Ib+TbGS7dnFfX34JzJtXsS5y5cnbbzOG\nleMZWOMikgv/fyXp6Y6GzNGjRI9LqSwa22xmtEIfKamM2O00krKy6JFGR5NS9pVXHNkTZ80ioNId\nkVFZIhVwaKjreZeUAKNG0ZjSS0oK1LTM3r08vxUr3B+7uJjj+uuv6U3faQ6yqIjKfPQtPnWLRSu5\nc07Z3Em/AT8/pmecxGq3qox2RosRx64fQ4+lPcr1FE8nnsbmK5vRc3lPzApyH02xK3Z8tfcrTA90\nrKQwWU1qOD2/NN8hV55jzEHL6S0hDAILgt3XhxstRtTyrqWe95jjY9yuV1G5fuM6nlz8JLZHbndb\n9nYl8wqOXi+/O+S+mH1uDZaqktvJd9vtzFg2bcpXLSGBVcQVCebExHyDoKD2SEtbCZMpFRZLLvz9\nayE09JXKn3wFpboUfIy+a5wQoq4QIubW/6EV3U9VLlWu4E0mR4a2YcN4i+rU4V9nZrWKyvnzcPCc\nw8I85+DLEz8/Tupr19IDGzfO9dxkmdKkSdpE+Oef/DtP54Xk59PLPXuWv7Vqpf22YQND1xUlSTl0\niNsMHsywfmWu76mnePzbBbCZTKx337TJ9berV7X8elgYFU55/JJt2/J87rSxitlMw7CyQMR//INp\nlSVLeB41a2qphqQk4gv8/bXxqe9eFxHhvv47K0szDiIj6cVXZDKcMYP8DkVFdGlkX/bDh3lsd70L\npLRpQ2OvMqyHFRV/fzZ7qkhE5w5FURT0XN4TfVb3AcCe68IgsDu6fCDo1dyrDL9vcA2/A6xRv5p7\nFX/4/qF2jSs0FaLehHpoPq05Tie6ltcm5yfDy+CFtza95VGhLb24FMIg0GBiA/RY1gPHrh+r4NW6\nl1GHRqlKPS4vDlMDpjp47O3mtIMwiDIR8wBQbC7G335/IyIrAoWmQryy5hUM2j7IY2jfndjstnKP\nU1lx5qSvqISG9oW/fx1YLNpcYbMVQ1GqD5BaXQr+LyHEJSHE30IIw62GL+OEEA2FEBsrup+qXKpU\nwVssNOE6deJE6ONDT8dgYHnQ3XffESIX27eXDxCrjPz6K9Qw6733akpEUagwn32Wn/fupZIpKWFY\n2lOo+NAhxxK/sWOh5qEBetg9enguA2zeHGpsqzIlWQCjCp9+6hjaj46moqvIPZO1/84E0iYT1KoE\ngM9SiPLr9iW4To8x+P57xu8qyh0A8N4JwaReZiYNs99/53jq0sXVg5YyaBDL8vLzNS77L76gwSGb\nvvz4I5+1vrRPRoeeeUb7LjGRSv/++xnmrkzoWhLMCOH6m9HIXHtZrWxv3KgaEp+MDLKRVDY1VU1i\ntVsRneOKjrbYLMgoynBZP/FmIkosJSg2F+Oemffgnc3voNhcjL3Re9F8WnPUGk9Pe3kIo0bF5mLc\nN+s+suPtd8+OZ7QYHbz69MJ0h8/ZxdkYeXAk/BP83W6fWpCKltNb4pdjv3i8zpSCFBXcdiHtAj7e\n8bHb6wOA7ZHbMfHURJd7sih4Ed7c8Kaau08rTMPq0NUw28yIzI5UIwyTT0/2eB7O8tmuzyAMAhFZ\nERXeprpEUWwOfeAtlhuIjPwIN2+eKmOrO5NqQ9ELIXoIIb6/tfSozLbVsVSpgrfZqMD69+eELCe2\nijZVkfLjjyxv05uDR45QyTiHPe9E8vLosTqHjxWFk3mHDiTL+UX3Ak+apCkc6Yl5klWrHEFaskOa\nPgKgf5l9fakEmzfXysqkWK1U1JXx5NatgxqFKEuysoj0HzVKwxLY7UywJSaylez4W1SgJSV8Fs7n\nYTSyoFWmS5KSGPlYoAt/jhhBLENlGgzZbDQWYmMZNfDyYpmkBBl+VcHyq+XLoVY6KAqNLHeKWpZZ\nNmrE6+7SRYtG/PAD446VCWEqClMuEhxZlrjDXQQFVU173okTeQ16lr3/koSkhzjkue2KHb1W9nLL\nAf/h9g8hDAJXMq+4/AawiUyzqc3QZ1UfvL3pbQiDwEM+D6HRpEZoMLGBCnjruaIn6k2oh4PXDlao\npt0/wR/CIPDzUUcAapdFXTx61Qk3E1BzfE18te8r+Cf4o8eyHi4K856Z98DL4HXbJDwA8OKqFyEM\nQm0w88WeLyAMAruiiCx/Y8MbaDy5MWJz3bPKXM647MI9MOfsHHRc0BHphenIMeYgNMODofw/kBs3\njsLPTyAq6tNqO0Z1KviuQoiRQogRQoiuldm2OpYqD9FbLMxnnznD/OFrr2nAoKwsIjIsFiJ9PXXV\neuQRekrFt8JXNpumHMtjZytLLl5kyLYidfh2Oz1NLy8aLD4+9LR27WKUQoKJymqfWq8et5cKQVHo\nCcrj+/gwdFwesQ9ARelsHJQlJhPw+ef02sozCqKjoYaKY2N5nqdP87t+FezFvHYt1x81quz15L0o\nKiIgrDLAO4AGhqIQhDd2bMXTGNnZ5C5wpta6eNHRmNq3T7vuF19kyZjBwCiPJ8XuLk+enOzaka8s\nWbiQx9XTBksIco8ejuvu30/jsTKSnU1jsyoqTvLzGUEpB1chveHWM1pDGITKwmaxWdyC5uyKHZ/v\n+hzCIDDqkOdxpCgKXlv3GoRB4OU1LyM5PxlXc69iX4xGy/zxjo/xxMInVMWaY8zBpXQNo3Im+QxG\nHByBTVc24fPdnyM8MxyPzX8Mm65sUs9lzPEx+HD7h3hn8zuw2NxXPPTb2A+1vGth2IFhEAaBNaFr\nHH4fd3Ichu4fekd13Pml+Q4KOjwrHGOPj1XL6fpv6o+6E+ricoZjE6+8kjxcybyiUuzqJceYg5dW\nv4Sv936N55Y/B2EQWH95Pf61/l9IK/SMaZIcUBcvls9e7Sx6f620lBlPN3ANKIqCGzeOwWKpvuqo\n6grRfy+EiBBCjBdCeAshwoUQIyu6fXUsVa7gX3mFt2T3bi1ELfnQv/4aKhpelnC5k7w8R+DcU09R\nqZYFOisuJtPcwoUcPWPHuipOiV4ODyeSvXfv8ifhoiItTPzKKzRMhGDv9Wef5f8RHsJcAQGeaUV9\nfZlrr1evYu1Dr1whArqscK5eZMi9Z8+KrZ+VpSmZFSuoSH/+uWLhfRnVeO218pHuisL7KDnXy6PA\ndRajkWOhY8eyjyENlfKkbl0aWXLdzEx63H/+SaVYXMx8fFlh+TZt+BylIWW10jBo3Zrja+/e8s9l\nwwailPT322wmeNMZF9GiBe+dc7/5/5bIcrwy0jR/+/0NYRAYsGUA5p2dh57LezrwuxstRhevdvjB\n4RAGgfZz22NXdNl1z2dTzqKOdx21R3u3Jd0gDMKl1ltK71W9HUhdBmwZAGEQ6Lq4q0vEwGQ1Ib0w\nHcIgPCL37YodUwOmos2MNqo33XhyYzw458Eyz3v0kdEYvHtwmQo/rTAN+2L2lWsUHI87jhUhK6Ao\nCn478ZtLTX6vlb3Uxjgzz8x02DYgKUAN7X+26zMM3DYQX+75EsIg8NSSpzwe86mnWEErA2hlETMC\nHKJz5gCTJzvarydP8vPbt8dNdMdSXQr+ihCioe5zQyHElYpuXx1LlSv4n3/mLaldm0jqZ5/VvKaw\nMKJ4b9xgLbmeaS0mxjNjQr9+LNkqyxOVdRovvaQpZL33abXy+0WL6EHLBiIVwQRYrfSgn3iCHvma\nNfTQduzgfnbtqlxeGdCY9irazMNup9KRVK/R0eUjzIOCGHJ2J1arK/lKUBBD0ufPO36fn+/ZuFIU\n4LHHUOEyOKuV4LeHHuI4qGgnPSmFhVBTP/qQtl7ZydTE3Lnl72/uXNe2rhI/MGYM91unjit5jl6c\n8+SKwujJDz9ohkxVppZOneI4WL3aMXx/7lyVNodBUJD7cR0Tw5RDGcbx9MDp8DJ4QRgEJp6aCGEQ\nHlHwUlaErMCj8x91qfE2WoyYeGqiQ+mWoih4Z/M7+HjHxwCAA1cPYOzxsS7tXdMK02CymrA6dDUG\nbhuolqWlF6ZjV9QupBemO4DwJLf9xFMTcTL+pEeUf+yNWAiDQOeFnRGXFwdFUdBndZ9yCXpaTW+F\nWuNrOZTZrb281iGF0W9jPwiDQGBSYJn7un/2/RAGgVxjLvZG78UTC59w8PQXBi/EW5vecijF08uB\nqwfwp++fKjDxRskNNJ/WHP9c9091HbPNDJ+zPioHf48eDLAePKhRg5RlZ8rWH08+yb/ffstijr17\nGfT7X/SCB6pPwYcLIerpPtcTQoRXdPvqWKpcwSsKSV880X96EndsaJWVq1c5wdnt9Hpk+dHRo0Dj\nxgz7S0VVWkolWZlStFGjCELThyZDQnjeL79cuXM9caLijT8ALTf8yCP8LFHzt8tcJoFnFakJf+AB\nerrucsRJSdxPu3YVP3ZBwZ15n5GRrK2XIg26yZMZun7+eY6nyjQn0ktWFp91TAwxEXXrEhPSqJEr\nW2F5cvo0gYbFnuubb0tkKuGTW6VSsivhoEGet7FaKz6jJiZyf0959uYcJC+PQE8dYDGlIAWR2ZEo\nNhdjc/hmGC1G9FjaA08uftKjd1piKcEzy57BD0d+QI4xB4O2DcKEUxMgDAKf7qpcTlZ2bnt3y7sA\nqLz/OvkXzDbPRmVYZhiaT2teLt2roijYGrHVI1bAaDEi1+gKaMwoysDwA4xUHIk9gpulNyEMAm1n\ntlXX8U/wx/CDw8tlmAtICsDmcEcX2q7Y8fPRn9VUw53KibgTEAaBdza/4/Lb1q3MGBqNjlNibi6L\nRoqLaQg0aaLxbcl+Ss5NEv/bUp1MdmG3EPQGIcRlIcToim5fHUuVK3jpSXfp4nkdm42hbr23sXs3\nlc6d8tSnpVEJ6sFtMqT44IOOE62kmN248faPV1pKZeAJ9W6zUfm3aVPxXtzuZNUqvim7boUujxwh\nB0B4OCfusohz3MnRozTHo6PJkleWDBlCBee8/9BQxt/WrSs/zWCz0cM8eJBREHfGTVwcFZDNpp1T\naChzzmXJ5cs04F57TWPQ06dNkpI4Hjwp2ZISplLcjb1332UI/8wZevKeiH/Kk2HDHElx7lSKijiu\nZcomN5dYkbLu1ahRvDd+fuXv32JhSqtnz4rVPklyn3IwIo/NfwztfNppXOOKHWGZYbArdiTlJyE+\nLx5eBi/0WtkLR2KPqMQwi4IXubRwLU9ulNzA00ufxpyzcwAAr659FcIgcDblLExWExacX6AC1wAC\n+AZsGVAl7VVlysAdsc+e6D3ovLCzGh2Yc3YOPt31qepJO0uOMQd5JWXnowtNhbDarcgoynCbWojI\nisCLq15EcGqwhz24F2cP3mikNy4xoxYLX71HH9W2kSSdCxdqbUPatePflSvp1dvtDAw6Bwvz8k6g\ntFQD4RqN1xAdPcThu6qQ6gTZPS2EGHVr6VaZbatjqXIFb7eTrvLkSdffZPMSGbfRM5/pt72TcKbk\nUR88mJ9fe43GgdclxwAAIABJREFUhrs8ua8v6+p/+aXsPuZSTp7U6qVnzWKMSl8/XVJCj2f4cO5v\nyhSNxU2I2ydtAbgvIRy9UtlnfuxY5ntlWV9lRBo/hzzwaRcX07hwB2Z7+WVuWxGQ4Lx5XHfkSHrE\nW3RtMvfvpyKpWZNGjCxfPHpUo8x1VyqWmMjwutFIo04IGpjODHGy1t3ZkFMUplm++w4eE4p2u1Yn\n/sYbLPV0x7YoxWZjmmqrk5Jo0IAzYVXK/PnEI4SHO34fEcEx71w9sW0b0LVrxb14mXqpSEe75GSO\nQzeMjiarCeFZ4VgUvAgllhL029gPfdf2xZyzc1Sl+/PRnyEMAo8veBzPLH0GPZf3RFZRFnzjfZFf\nyrFXYinBeL/xbrvRhWeFo71Pe2yPdO1WOHDbQNSfWB9D9w3FxisbYVfs2H91P4RB4KMdH8Fmt2HQ\ntkEYeWgkhEE4hKj1kl6YXmEFOWTPEDXHb7PbEJAUAIvNghxjDsYcH+NgWPx09CcIg8CqS67ASbti\nR4NJDdB6RmuciDvh0l72csZlfLD1A3gZvPD6+tcBAKcST7lgESTvwC9HPZf0VURu3OBrKguj7Hag\nVy9ggI5FODGRvtrBg9rU9+qr9IVkJXBpKfDee/z/7FkrFEWB0RgDPz+Bixef1e1rEvz8BFJT3ZMR\n3a78X7OZ2xWpxN2JnEiPHKFp50xeEhODSoUF9RIczLiQRIDXqcMSqi5dCEpyzt9/8QX7XUtzc/Zs\njlpJOmI2O26Tnw8HYODEifRE9dcgoxcPPURlIgSVS1QUiXAqKp7y0s5Ar2vX6IUfPsyStJdeorfa\noAEVqV7mzCFewNkb27ePJrknMh6pmN2xEIaHE9NQEQ/v8mUaBO5AgrKvpBCkH/7qKyqX2FimEKZP\ndx+d+PZbTTHHxXnGUyQkcB/Z2Y6Gigxr9+rFCIW+fG/lStcc/ttvEztRVrhdViQ0b+4YoUpJobtS\nla1Yvb15LOeSSlnW9/jjfM8qwyJYXMz7f+IEjSp3Db0TEyvVZa/nip4qoGvuubloPaM1GkxqQAW4\niCC3TeGb8OaGN/HO5nfUdT/ZoTG1WWwWFe3tDsh29PpRCIOAt79r6aosdXtlzSuYFjgNcXlxMJqN\n+Mv3L0TnRCOvJA/CINBxfkdcSLvg0VtuOKkhhEEgPq+ciNctuZh2EemF6VhyYQmEQWDmmZlYEbLC\nhRXv+RXPo7Z3bWQUZSA8MxxPLX4KO6LIiKkoCj7Y+gEG7x6sMu8Vm4ux+MJieBm80H1Jd/V+/XT0\nJ4/nMjVgKoRBYFEwO2ZOD5yO9ZfXo8BUgLc3v41tEY7VSVa7FZlF7um3CwvZgqF1a8dOy5cu0Q+R\n05fVyml12jTNply7lq8iwKDt++8X4tSphrh8+VXY7RZcuzYC2dmaI2SzFSMraztstqptYVylCl4I\nUSSEKHSzFAkhCit6oOpYqlzBf/klb8nly66/LV1KT8tTHbSiMHTrvO3SpWSI84RWBxw71em95thY\nTVHbbFTMJ0/SixSCI3LMGA0Jfv/9HKGNGzsaGopCJaf3Ap1DuleuaMdNSaGCqCyznMytTphAkOCm\nTQwLl5RQOcg8eH6+dvySEg1vkJTEBjFt21JxymoE6Y1VlugkPZ3lZRWhco2KKr8hDOCqcEpKqFB/\n/FGLSnzwQfn7iY/nbFGWR62XLl1o+Mn8f0kJgXDuSh0bN+Z5lAXsPHPGVQHKSIIQjrTF0ni9Xdhw\nYiKNUf3zCw4GXnjB1YOfMYOkR7JqxLnffVkiGRw9lUcWF9OwbdeO98ZqpeH273+7rFpiKcHljMv4\n/vD3eGTeIypC22gxIik/CZNOT3IhlzHbzGrb03+u+yc+2vERIrIikHgzEcIgUMu7lkdimezibCiK\ngsSbiQ7h7k93fYq6E+piwfkFJL7Z942KOj+VyGhh7I1YZBeXbbQ0n9YcDSY28FjTfirxlIpq10tU\ndhT+uf6fCM0IhdFixIqQFQ519Z/s/ASPzn8UJZYSfHfgOwiDcNvb/uj1o2oTnu8Pfw9hEHhj/Rv4\ncPuHmHFmhsv6AUkBaDG9BfZE74HFZkFQchBsdhuMFiOEQaDl9Ja4lH4JwiDQb6Pj85a19s6ld1J+\n+IHDRB/AlNQnlQnA2mxGBAU9iIiID6EodkRGfoz4+HHlb3iH8n8e/O3KggUsYZLo3qQkx1FQnpjN\nBOlt20agXps22mS7aBGVpjtv7vx5x5rvXbuomPTepZxku3dnbnfiRM0bW7GCk7+vL/fx1FMs5+rf\n31VpZWdT0UZHM+erN0gGD2Zk4HboP0+epFncsKGWvHr8cf59/33Gxpo1Y1pBCEYhAHrx+hC0rJkX\ngpM9QEXtrAg8SV4eMRLuctJpaRr9bHg4r1WmDerV4z10lpwcPk+TSTu3Y8fodTt7nyYT0x9lNVUp\nS0pKqPTefts1TTRkCEsjK0IWdP582SA9CULTdwoEGLF56SUaLPpITF4eOejL4zHYsYO5cudcuiw5\nXaYDf8mOfp7K1TIzXe9veaIojLB5ap4k+38+/jiNZNl0R19qeEsG7x4MYRDwT/CH1W5Fw0kN0XBS\nQ1UBBqcG46XVLyEyW3u/FgYvhDAIzA6ajcUXFkMYBEYeGolCUyHOp54vs0YbYM249Mal4TB0/1Dc\nPe1uJNxMwJyzc5B4MxHrLq9DO592KjI/oygD982+D7+f+N3jvq12K5ZfXI52Pu0w8tBIl987zO0A\nYRBlnuOGsA34dv+3GH5wOM6lMLVVai3FsovLkFGUgSJTEX448gPCM8PhG+/rsWucXbHDP8FfRcgf\njzuOR+c/iotpWmG55KxfFuIKGPRL8FN5AS6mXVTTIFIWBi9Ep4WdPF6LohB206+f9qpevcrhabMx\nY/PRRxWv6gUAq7UIfn4CZ8+24zXazbh+/WfcuFFJVs8KSFV78F5VsU51LNXWbOb6dTKXSfhkWeU7\n+rClrN9+9lmti5wQ9LKaNOH/7mqtg4KghsQ9iaIwN1oRLxOgMSEEw9tSJPnI228DixfzfxlzstuZ\nN65IPt+dyB7xTz1F5eDnx4leCHrl8l4IQWUqjyu76kmudauVCnTRItfc+eDB3L+nsG1xMY0aIRzz\n5ACVXs2aTEGcOqX1D2/ShAk3g4Hw2NJSbbKXHdaEIJvcpk00Us6e1YppPfHV+/tz39td86oeJSND\nO959991+v4LyZMcOHuOFFyq33ZkzvFfbtnEmDApyTPPUrMn9Nm3KHgkSmJmdzfGWk8MqgbFjuX1I\nyJ0DU29Hhg5luiIhgam3Y6487Xuj9+LlNS+rod5B2wY5oLGnB06HMAisvLQSABXovzb8C+3mtENI\negjMNrOq5NvMbFMmyG70kdG4a8pdiMyKRMvpLVHbuza6LelW5iVsvLIRvVb2QmZRJhJuJkAYBJpP\na+6xlj4wKRA1x9dUz8fd76surcKa0DUYeXAkvtj9BRRFQXZxNk7EnUCRqUgNpwuDwMBtAwForW71\nRsP1G9chDALdl3Yv8xqkzDk7B8IgXFD1m65swplkz6XAgUmBKhOfnhdfURS37H12O+3JmBjNvly4\n0HW/q1fzt9919tKWLcyqnTzJYJo7kpuSkjiYzRwvRUVh8PMTuHDhNrBF5UhVK3j/W+x1Dzh9X0cI\n8YoQYq0QYnBFD1iVS5Uq+ORkKuadOzWvsndvevTPPUflMXo0Q3rScz5xguvpKTRPn2ZoOz+fHt/e\nvQzHyonbnQfv788w/tKl/Oznx9FVVs/t8sRi4WjU7yMvj0ClSZM4ue7bp/2+c2f5RkZZkp9PpTRk\niOP3/v5UrgEBvF+xsa7XVV79c2wswWtPP00v25MRIgFpQvBtlCLTD61aMT736qv8/OOPUKMrgEYn\n++mtkqYjR1he9sYbrjX5S5fSW/WkoCRKp0sXx77r7qS0VIvWZGRwFureneeSlcXfyqoymDmTxo8s\nsfz+e21/gYFAy5aOvA0mE2c2fepCkvjoEUd6URSej5cXr0sab40bcz8mE6/59981zn8ZpZGSnQ0V\nN1BRSUrivdi8+c6a1igKo2TLl9PoqmDVRkBSgIuyyCjKQF5JHs6nnsfIQyNxz8x7EJEVAWEQeGLh\nE+p6haZCtPdpz65v512BVqXWUljtVgw7MAx1J9SFb7wvhEGg4aSGeG3dax7PKTI7Eq+vfx3CIHA+\nlVBuCXbbG+O+dHRn1E4q4oMjPTZqkS1h5RKdHa1S6r618S0Ig0Dvlb1x3+z7MOn0JMTkxGDs8bEY\neWikSsID0NgZdXgUdkY50sWturQKtb1rq6mFyxmXEZYZBkVR0GNpDzSe3BhZRQSkymiGvgRPv39F\nUVRqYGEQ+Gz3Z+rvUwKmQBgEDsc6NgeTftSrr9IH8fd3P6QkWakertK9O7eVvb3K6zSXn882sgEB\nLcpe8TakqhV8PSHEMCHEGSFEuhAiSggRL4RIEkIs/1+i6atUwUt6omHDGFqvUYOfGzbkpCYBbUJo\nZVLBwQQklVeqpiic9OSoOHyY4eyuXRkj+uor7vfXX5l7lPlHfQtVX1+GSCtaTqYonj1dWf+tpxHN\nzKRB8/LLt+/FO0t6esXIYOx2evSeSqAkAdHy5WXXoM+dy2f32muO6PiCAnrs69fzc79+fGPtdkf6\nUz8/gvyee+72WkvpRRIiCeHY/MVZ8vJotPTty/sln+8PPxBAGB/PiMcHHxCM+MYbrvuQufO8PI2T\nQeInZEe6mTo2sN9+YyRj3Dgy0Pn783qbNGE5pidZsIDHF4JjceZMrUuhPo9tNtMAOnvWdbxmZ1cu\nBSR5Alq0YBXA7Rq9MjpSrx7/Dh3q+ZCJp9BtSTdsurKJueIN2j3PL82Hl8ELnRd1BsAcdG3v2kgt\nSEV4VrhLM5ZcYy6WXVzmkvsusZSg4aSG6L6EXq4M/UdmR7qEnKVY7VasurQKLaa3UHPM8XnxSCtM\ng9VuRWR2ZJkMcpIe1pOYrCb8cOQHCINAzfE1kV6YjmPXj+H9re9j+MHhuHfWvSroTrL2CYPA57s+\nR83xNfHqulfRdXFXldbXZrchvVAzjFdeWoma42uqDXBqe9dG3Ql1AUA1WLot6Qar3Qq7YseSi0sc\n2O0AGk2NJjVC37V9kVGYoZ7r8ovLcdeUu/CH7x9YHboatb1rY8TBEQ7bWiy08dx53+VJeDhxoSYT\nA7zlTcP5+Wfg5ycQElLJKFkFpDrL5GoLIdoIIZpWZrvqWqo8RH/1KienGzc4Qf7wA8ORubn0duvX\nZ4jxTmk29XnmtWvpZU2ezBI1Icg2t2MHR1FpKT3Xu+7ibxUh0zEaSSLi5eUIpDp5korPbOaELCMG\nAK/x6ad5DGcv/HZEYgbee8/x+/376RXrmf+kt6tnXJs5Exg4kG9lTg7zwuUphg8+4H70+WtFcQXn\ntW1Lz9PZ++7VS3suzmDKV19lSLsiBtakSRrnv7e3I+ve7Nk8joxaFBVRQUua5PnzHfeVm0tj8Isv\nqOCcO+YBxBbI1E18vCNSaMwY7nclQ8koLdWu8e23+ffgQf5WXFz+PQ4KYlQr8BZTWVYWDZhlTrnS\nOXO47/L4QCsicXHAP//JtNedGF779tGQFII5eA+GuQy/rwhZgY93fOzAE2+xWfDautfUxi7Zxdku\nhDF6Bd1/U38Ig0DdCXUdWrZabBZ0W9INg7Y5kvtkFmW6MNpJOXTtEIRBoMfSHhh3chw+3fmpGnIv\ntZaN1N4dtRu1vWtj1OFy+i2AXPf6lEKrGa1QY3wNldP+wNUDeHPjm1h2cRmGHxyOpxY/hdretfHY\n/McgDAIHrh5QIxOydt+dTA2YimmBjG55+3urVQZNpzTF8yvcjHOQhKedTzt8uJ0VQ3/4/oE+q/rg\nVOIp1PKuhR+O/KCmCAZs9RCN0kl6OoeWmyyNg7z2mjY1uxNFscNovOpgYFmtBXfE4+9J/g9kVx1y\n9SrUsL07sdlo3sXHM8eoZ5k7f55h0tmzqdDffJPNQMaP1+hLH3qIykyWfAUF0dzMydFym5L5a+NG\nKqjevd2HiOVobNlS8+QsFn53112u6/v787fPP2eYXY+g1su1awx9V6RDWG4uvWRJpRodzXyn9Chl\nyFhGE9q3d0S1dOnC77Oy6JlWpPlJdjZr4teupSd+771aXbo+F15URAUbGEgKX8lYce4cFeLRo677\nbteO91P/wqakUGEOH87Ih4z3ffIJj/nuuxonZmoqn5VMD0RHM20hKwWCg9kBsKyZxl2o3mwuO0qS\nl8dZ6cUXGcafN4+phXr1OMbMZhogf/7pOVVy9mzlWwD7+tIQcC4nlXLtGvESlUEyeZIJE3ifKwpu\nlBgEd+WTIAgsOicaJ+JOuOSFnUWSwqQXpiM6J1o1Dg5cPQCA+WUZpj947aDH/QQkBeChOQ9BGATe\n2/Ke23WMFiP+9P0TYZm8Z+192qOGoQbeWP9GmeF5ACry/qXVL5V5PZ62/Xrf17Db7bArdtQYXwNN\npjQBABU5f/DaQZhtZsw+O1sFGq66tAqPL3i8XJKfeefmod2cdqgxvgZaTGuB2t610XdNXyy+sNij\n4TJw20B0WdRFDcfPCprlUNGQV5KHHGNOuYaPpNL417/Kvgd33831EhJoJzZv7mhHJyZOhZ+fQFbW\nFo/7qCr5PwV/O5KeTvS3PiwOAFOnMmRbUMDYjqyhPXOGylAqg+ee4yTzyy+8rYMH8/8lS7ScpMxf\n6pe6damQ//yT+/n8cyoS2QymY0cqp/r1OTmHhTGcK/enb/CRkkIlMGoUDYDBgx3LqObPd588ioqi\nAtu4keV8zlECu50AP1lfsnix6z4WLeJb8PXXDJM7gwH1TT6kF3bqFBXP66/z3C5c0HLd2dk819hY\nnlvNmlSmW7fyvjuXIxqNvFZF0RrPyFBskybac9q7l6mR2FgNaLhqFbeLjnZvMKWk0FiRIX5AM/j6\n96eRULOmVvImqa5k2dx999E7HjgQKhBRjoXnnnM8VmkpIyj6nDlAjIT++FLuu4/3W0pqqiu7X1ER\nz08ydXz8Mf/KZkKS48EZmChFRiP0hkRWVuXYB51FGnpTptz+PqT89Rcb5JRViuos+fnlnr/sJFdW\ny9ZxJ8eh0aRG6LehnxpivmfmPfD294bJasLY42NR27u2Axe9O5EI/Moo4SJzEfJK8rA3Zi+aTW2G\np5c+7VAyZlfsCE4NhsVmgV2x42LaRdhvE9T45Z4vUXN8TTSY1AAjD43ExFMTATDVEJwarHqqEVkR\n6Lu2r0P3u/Lk6aVPQxgE+m/sj+5Lu6PD3A5q85inlz7t1kB4ZtkzaDipIbKLszHu5Dj8euxXXEi7\ngG5LuuF04mnkl+aj5viaeHpp2Tpixw5myDZv5tTjif07IkKjA5EkopL7y2YzIi1tOYKDuyItbRns\n9kr2qKik/J+Cvx2R5C7OdJ7SG9YzaCmK1gJWhrkHDWIIMT2dueJWrTQlM2eO9rlBA/59+WWSt9So\n4UgkM2AA1+nYUcsXyjp3g4GNcOR5SgMA0Lzwb79lWZo8tqeIg7P8/rtmVNSqRWDali0aIl4I1utv\n2OBYORAYyLyvJGp+7jn+de4El5/P/elxAbLSYMECbcIXgm9dWpp2fSNH0hu227U0wkEnb2jECH4v\n+ektFu5DUpw2aULDQnr0hw/zOcbF8a/sEujjw3PUn2dgIH/75ht+Xr2a46JHDz7b4mL3NfqyNaz0\n7GXuW3LxP/20K2ucRAI5M/s1asTvnUPUffrQSJLSogWVuTN6KCeHRteECXwW+t/T04lzuP9+92Hr\njRv5jKTs3s1zcW50UxmxWplK8RR9cD5Hk4lGoCdq4vKMDZuN74gzWY/Vyt/On3eJTB27fgzrw2hU\nhWWGoemUpmgwsYEDSC0kPQTCINB0SlMix5d0x5jjY1R2tz99/0T9ifXx7x3/RlZx1q1TVdTe79rp\nK4jKjsLykOXqepURRVHQfFpz3DtL63K59vJaCIPApNNkBTRajC6tYzOLMtFtSTesCNHKFePy4vDd\nge+QnK8Z+l/v+xp1vOug8eTGHklk9PckKd+VL+Rw7GGEpIfAardi2cVlOBx7GP/Z+R/4nPXBP1b9\nQ416WO1WbAnfgt4r2UVP1s/rxWq3qriGV9a8AmEQMPgZ1OiByWpCzxU9Mfxg+RTLZjOn3Bo1OPVV\nBMupz2RFRX0OPz+BmJhv4ecnkJJSgUZRdyDVxUVfVwjxsRDidyHEOLlUdPvqWKpUwVutzA/Hx1OR\ndu+u5es2baKi7NePSkbmej15PAAjAcOHs55deky//cYJPylJAwvpJyYJ9JPebq1anLBDQxm+lZ57\nnTpUDD4+DIUCRH506kRvWAhNeZZ1jnqRCqRNG/6VoeRFi6jYJNmMc/vPpUs1xdykCZXdRx9VrOHy\nsGG8vvR0RiaeeIL58eBg3ueff3bN4T71FI2coiIe69NP+dz8/fl80pxqX1NTCU7r2JETuc1GpR4V\nxdy3TEeEhtKACQigMXbffRpPPsBt5DOTRl9FSxadpaSE98cdlkP2pv/qK8fvZ892z+anl8JCjpk2\nbbRxZTTy/2XLtLy5O3nrLR73xRd53YpCQ+b4cWIP9Ar+4kXen3ffdU2d2GwsNzzsiGCulCQn81ze\nekv7ThoVn33muK6iuE/fXL1KwKDsPS+79P31l7aO1crxJ8e2GxbKK5lX0HZmW/xj1T9UQJdzI5Yc\nYw7Cs8LRbUk37IjagYisCAzdP1RV1BK4Jo0FScQyO6hiBlKptdSh3l5KganAAbxntBgduq/F5MSg\nz+o+OJdyDkXmItSdUBfPLn8WRosRrWe0xv2z78ek05MgDMLBMJBh77nnylZUN0puuIAHc4w5EAaB\nh+c+jBUhK/DelvdQYinRUPGz2sI/wR/CIPDovEfVqMX7W99X9zH33FwIg8Ccs3Pgl+DnEHrXS64x\nF21mtsFbG9/ClvAtsNvtiMmJ8bi+FLOZj/pjNvOD3c4hLqcxPe4WYJapoIBDbeNG16xTfPw4+PkJ\nhIcPwpUr78JodKUjrkqpLgV/RAixVQjxqxDiJ7lUdPvqWKo8Bx8bqyk6IYi+qFOHk1zTpvS+pLIW\nwjWcX1JChWE0coITgmC2pCSGg6VXmJrKdIBz/jE0lICqDRvocd286WgqjhjBCVyGTN95h0pHMqlJ\nj3HoUP7+/PM0Ftq29czhHRNDZbJnj8ZrL4FZNWtq7Uffeovhd2dedUVheuGjjxiudscCKCU7m/tO\nSGCUw53B4CxGI73wU6e0Ov733qOCl6mPf7rn31bFZqOnK5VDcjLJhJwnfHk9L71EY6ppUw0BL2u4\nV66kd1kW8c7169zOnZJbtozpln37qGCcKx2Ki2m4TZzomPeWlRXSqHBugyW/69CBzwLQYokytVJW\nH/rMTAIC33mHaaPz57lNhw7868wOJ6m/9Ar39GkNf1BWi1p5j1au5P1o2NAxipWXRzKa337TDJV/\n/5v7lQZtTg5TQvK+yEZGUiSrneygFx/Pa9CT59y4oQEcv/wS55aOw93T7sbUwKmql+6X4AdhEPj9\nxO8YdmAYrt3QysHOp5zHJzs/wfkUx64jvVf1Rh3vOojKjsIj8x7B5NOTsTViq+o9jzg4glzy2z9y\ne2vsih1phWkYun8oTieeVg0CfWvYQlMhanvXLjcELcVkNeGpxU9h0PZBGHVoFIRBoLZ3bZxLPofv\nD3/vEFIvNBXi+0Pf4+U1L3ssqcsx5sDL4IUXVmoocbPNjE92fIIXVr6AOhPq4K4pd0EY2OdeURTM\nPDMT2yO3w2Q1YUrAFAQlB2Fj2EZ8vONj+Mb7qvu5nHEZfdf2RXhWOOyKHWsvr8XQ/UNd8ulphWmq\ngVBqLcXu6N0O9fDuJCOD2cuaNR2LiHJzGcASglNzaCi/v3iR3739tlbt3KmT4z5LShIQEvI8btzw\n0DK8iqW6FHxERdf9by1VruBPn9aUtwxXH2DYCKWlnFC9vekhSc94/nxORmlpWlnUjBlUlN9/r3Uq\nGzmSoXNF4f9y4gWo8MqihS0p0TzJwEB6HTKHGxurka7IMHFcHCfpV1/VSGY8MZvJws4lS7Tvjh5l\nvMrLi/vcts19wxQp9etr5/P9955rwyX/+O+/ayxifft63q+8XiFYnpWdzdZP48drKO1vvuG5nT7t\nOQdrMjHd8dhjWi12t268557O1WLhc5WKLTSU2w0cSMX555809oxGGnU1ajBaA3DM6JULQKPijTdo\njMgx1qkTY4N6VkKAhp+M1Bw6xPsfGUljaPRoGh716hEw6SmHrShaukQIjaCnPBk6lAZhbi7HREAA\nDRVnt2bbNmJF9EgjicqfPLl8wJskJJIpJ+fxOX06x3D//vw8ZgxBk5KlLjubhsHLL3P8uwPz5eV5\nDt1nZGjg1VtslcfjjqsK47nlxEYUmArw5Z4vcST2iEsL1BZTW6h16/029sPd0+5GSFoIPtnxCTrO\n74jg1GAIg8CXe75EVnEWjl0/puaqe63sBWEQLvnlHst6ONSiv7flPfzt9zcemP0A1l3W8DNmmxnP\nLHsGQ/ZWruLF56wPhEHgtbWvqcC71aGrMf/8fMTeiMX1G9fx7LJn0WdVnzIR8LI17ncHvkNoBrWh\npOTttqQb2s9tj9fXv46D1w4irySvXK/ak8j6fmEQKriw1FqK55Y/h1GHR2Hy6ckw+BnU8j2DnwEA\nEJ8X7zbqsXcvH/k99ziG4n18NJ9ICPoyAH2sfv043BWF61WkoWF1SnUp+GVCiC4VXf+/sVS5gj9w\ngB583770AP74gxNvYCDDlXY7FcqHH2oT3uef8zaGhXFSa9WKnPbOcv/99L7NZm1y8/NjeLpWLXoj\nejEYCH5KT+dE9NZbnMQGDYKaK5blYNevO07ef//NdQYNYkyprP72hYWMDLRu7eh9m0wak9r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ao3Rh4aCbtiR4NJDdBiGhW/bMCib7ICUDk9vuBx9NvYD6+uexV1JtRBXon2TkfnROPD7R+qoDW9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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(8,6))\n", + "red_patch = mpatches.Patch(color='red', label='Genes without TATA box and Inr')\n", + "green_patch = mpatches.Patch(color='green', label='Genes without TATA box but with Inr')\n", + "blue_patch = mpatches.Patch(color='blue', label='Genes with TATA box but without Inr')\n", + "yellow_patch = mpatches.Patch(color='yellow', label='Genes with TATA box and Inr')\n", + "ax.scatter(np.arange(len(df['gl'])), df['me'], c = np.array(['r' if TATA == 0 and INI == 0 else 'b' if TATA == 1 and INI == 0 else 'green' if TATA == 0 and INI == 1 else 'y' for TATA, INI in zip(df['EPD_TATA'], df['EPD_INR'])]), s=1)#, alpha = 0.5)\n", + "plt.xlabel('Genes')\n", + "plt.ylabel('Mean expression (log$_{10}$)')\n", + "legend = ax.legend(loc=\"best\", handles=[red_patch, green_patch, blue_patch, yellow_patch])\n", + "plt.savefig('figures/ExtDataFig3d.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "\n", + " \n", + "\n", + "
OLS Regression Results
Dep. Variable: bf R-squared: 0.008
Model: OLS Adj. R-squared: 0.007
Method: Least Squares F-statistic: 9.308
Date: Wed, 19 Dec 2018 Prob (F-statistic): 3.45e-10
Time: 18:55:54 Log-Likelihood: -5486.1
No. Observations: 6935 AIC: 1.099e+04
Df Residuals: 6928 BIC: 1.103e+04
Df Model: 6
Covariance Type: nonrobust
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coef std err t P>|t| [0.025 0.975]
Intercept -0.3045 0.065 -4.709 0.000 -0.431 -0.178
gl -0.0365 0.015 -2.463 0.014 -0.066 -0.007
EPD_INR 0.0689 0.115 0.599 0.549 -0.157 0.295
gl:EPD_INR -0.0148 0.026 -0.567 0.571 -0.066 0.036
EPD_TATA -0.2386 0.189 -1.262 0.207 -0.609 0.132
gl:EPD_TATA 0.0233 0.044 0.524 0.601 -0.064 0.111
EPD_TATA:EPD_INR -0.0952 0.055 -1.720 0.085 -0.204 0.013
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Omnibus: 1116.572 Durbin-Watson: 1.952
Prob(Omnibus): 0.000 Jarque-Bera (JB): 1864.665
Skew: -1.072 Prob(JB): 0.00
Kurtosis: 4.363 Cond. No. 145.
" + ], + "text/plain": [ + "\n", + "\"\"\"\n", + " OLS Regression Results \n", + "==============================================================================\n", + "Dep. Variable: bf R-squared: 0.008\n", + "Model: OLS Adj. R-squared: 0.007\n", + "Method: Least Squares F-statistic: 9.308\n", + "Date: Wed, 19 Dec 2018 Prob (F-statistic): 3.45e-10\n", + "Time: 18:55:54 Log-Likelihood: -5486.1\n", + "No. Observations: 6935 AIC: 1.099e+04\n", + "Df Residuals: 6928 BIC: 1.103e+04\n", + "Df Model: 6 \n", + "Covariance Type: nonrobust \n", + "====================================================================================\n", + " coef std err t P>|t| [0.025 0.975]\n", + "------------------------------------------------------------------------------------\n", + "Intercept -0.3045 0.065 -4.709 0.000 -0.431 -0.178\n", + "gl -0.0365 0.015 -2.463 0.014 -0.066 -0.007\n", + "EPD_INR 0.0689 0.115 0.599 0.549 -0.157 0.295\n", + "gl:EPD_INR -0.0148 0.026 -0.567 0.571 -0.066 0.036\n", + "EPD_TATA -0.2386 0.189 -1.262 0.207 -0.609 0.132\n", + "gl:EPD_TATA 0.0233 0.044 0.524 0.601 -0.064 0.111\n", + "EPD_TATA:EPD_INR -0.0952 0.055 -1.720 0.085 -0.204 0.013\n", + "==============================================================================\n", + "Omnibus: 1116.572 Durbin-Watson: 1.952\n", + "Prob(Omnibus): 0.000 Jarque-Bera (JB): 1864.665\n", + "Skew: -1.072 Prob(JB): 0.00\n", + "Kurtosis: 4.363 Cond. No. 145.\n", + "==============================================================================\n", + "\n", + "Warnings:\n", + "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n", + "\"\"\"" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y,X = dmatrices('bf ~ gl*EPD_INR+gl*EPD_TATA +EPD_TATA*EPD_INR', data = df, return_type='dataframe')\n", + "model = sm.OLS(y, X).fit()\n", + "model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Hn4MdV3Y41GTtQW/Uw2A0QFEUGyEZmxGLXz1/xZA9Q1Bnah1EpkbC76YfSEt4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SBVdruu9zdzHN56i9f4yBH+/vz5td6AmeiakGA40D9/WgyvzXgNru6uOP7ouMFe77ChA5Iy9Heu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\n+MD9/QoL+b3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98eE2d/2KaSem4dox16oCnWBhU9wmkInw7Ipn4ZAcuGbkNWg0qhEajGgA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\nAksLb9okr7Nai+BwXB5CbtDLAbViQWH+7q9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wH8CHD01tSfEEBeVVVJQKhYJHp+dfxIuN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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(8,6))\n", + "red_patch = mpatches.Patch(color='red', label='Genes without TATA box and Inr')\n", + "green_patch = mpatches.Patch(color='green', label='Genes without TATA box but with Inr')\n", + "blue_patch = mpatches.Patch(color='blue', label='Genes with TATA box but without Inr')\n", + "yellow_patch = mpatches.Patch(color='yellow', label='Genes with TATA box and Inr')\n", + "ax.scatter(np.arange(len(df['gl'])), df['bf'], c = np.array(['r' if TATA == 0 and INI == 0 else 'b' if TATA == 1 and INI == 0 else 'green' if TATA == 0 and INI == 1 else 'y' for TATA, INI in zip(df['EPD_TATA'], df['EPD_INR'])]), s=1)#, alpha = 0.5)\n", + "plt.xlabel('Genes')\n", + "plt.ylabel('Burst Frequency ($log_{10}$)')\n", + "legend = ax.legend(loc=\"best\", handles=[red_patch, green_patch, blue_patch, yellow_patch])\n", + "plt.savefig('figures/ExtDataFig3e.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "grouped = df.groupby('group')\n", + "cut_series=pd.cut(df.sort_values('gl')['gl'], bins=6)\n", + "cut_series.name = 'cut'\n", + "df['bs_notlog'] = 10**df['bs']\n", + "df = df.join(cut_series)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Inr and no TATA: n = 2035 genes (942, 531, 442, 74, 46 in each quintile respectively), No Inr and no TATA: n = 4397 genes (2585, 1124, 635, 36, 17 in each quintile respectively), TATA and Inr: n = 144 genes (53, 45, 24, 19, 3 in each quintile respectively), TATA and no Inr: n = 359 genes (129, 126, 58, 31, 15 in each quintile respectively), " + ] + }, + { + "data": { + "image/png": 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FAAAAwDCEWQAAAAAMQ5gFAAAAwDCEWQAAAAAMQ5gFAAAAwDCEWQAAAAAMQ5gFAAAAwDCE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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, subplots = plt.subplots(2,2, figsize = (20,20), sharey=True)\n", + "subplots = subplots.flatten()\n", + "for (name, group), ax in zip(grouped, subplots.flatten()):\n", + " cut = pd.cut(group['gl'], bins=5)\n", + " print('{}: n = {} genes ({}, {}, {}, {}, {} in each quintile respectively)'.format(name, cut.size, *cut.value_counts()), end=', ')\n", + " group.boxplot(column='bs_notlog', by=cut.values, showfliers=False, ax=ax)\n", + " #ax.set_suptitle('')\n", + " ax.set_xlabel('')\n", + " ax.set_title(name)\n", + " ax.set_ylabel('Burst Size (inferred)')\n", + "plt.suptitle('')\n", + "plt.savefig('figures/ExtDataFig3g.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "SpearmanrResult(correlation=-0.46167635288576997, pvalue=1.5255937336569122e-13)\n" + ] + }, + { + "data": { + "image/png": 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ZXpyum80G4KNF9o2I9cD6uSVzOJLaEdGaxLHL5nNtJp9rM43rXMts89gELJe0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\nAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from scipy.stats import spearmanr\n", + "df = df.sort_values('gl')\n", + "l = 50\n", + "plt.plot(bin_array(df['gl'], l = l), bin_array(df['bs'], l = l), 's', c='black')\n", + "plt.ylabel('Burst Size (log$_{10}$)')\n", + "plt.xlabel(r'Gene length (log$_{10}$)')\n", + "print(spearmanr(bin_array(df['gl']), bin_array(df['bs'])))\n", + "plt.savefig('figures/ExtDataFig3a.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "SpearmanrResult(correlation=-0.10276849552896372, pvalue=0.2320792746547986)\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from scipy.stats import spearmanr\n", + "l = 50\n", + "plt.plot(bin_array(df['gl'], l = l), bin_array(df['bf'], l = l), 's', c='black')\n", + "plt.ylabel('Burst frequency (log$_{10}$)')\n", + "plt.xlabel(r'Gene length (log$_{10}$)')\n", + "print(spearmanr(bin_array(df['gl'],l=l), bin_array(df['bf'],l=l)))\n", + "plt.savefig('figures/ExtDataFig3b.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def toArray(gene):\n", + " return np.array(np.int_(str(gene).split(',')[:-1]))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "exon_length = pd.Series([np.sum(end-start) for start,end in zip(gene_annotation['exonStarts'].apply(toArray),gene_annotation['exonEnds'].apply(toArray))], index=gene_annotation.index)\n", + "gene_length = gene_annotation['txEnd'] - gene_annotation['txStart']" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "c57_UMI = pd.read_pickle('data/SS3_c57_UMIs_ML.pkl')\n", + "c57_UMI = c57_UMI[c57_UMI[1]][0]\n", + "c57_UMI = c57_UMI[~c57_UMI.index.duplicated(keep='first')]\n", + "c57_bs = pd.Series([gene[2]/gene[1] for gene in c57_UMI], index=c57_UMI.index)\n", + "\n", + "df2 = pd.DataFrame([c57_bs, exon_length, gene_length], index=['bs', 'el', 'gl']).T.dropna(how='any')" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def check_ranking(arr1,arr2,bs, l = 20):\n", + " mat = np.zeros((np.int_(np.floor(len(arr1)/l))-1, l))\n", + " for i in range(np.int_(np.floor(len(arr1)/l))-1):\n", + " median = np.median(bs[l*i:l*(i+1)])\n", + " ratio = arr2[l*i:l*(i+1)]\n", + " mat[i,:] = (np.array(bs[l*i:l*(i+1)]-median)[np.argsort(ratio)])\n", + " return mat" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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BkAQAADAQkgAAAAZCEgAAwMDFZAEAYB9V1eR9XVB+PQlJAACwj7YLPlUlEJ1EdLcDAAAY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\nkiRJkiSpY5EkSZIkSR2LJEmSJEnq/H83AdZ8QFP3lAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df2 = df2.sort_values('gl')\n", + "plt.figure(figsize=(14,14))\n", + "plt.boxplot(check_ranking(df2['gl'],df2['el'], df2['bs']), showfliers=False)\n", + "plt.title('Genes grouped according to gene length')\n", + "plt.ylabel('Distance from burst size median in group')\n", + "plt.xlabel('Ranking in group for transcript length (short to long)')\n", + "plt.savefig('figures/ExtDataFig3c.pdf')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Figure 3a-d, ExtDataFig 5a-f.ipynb b/Figure 3a-d, ExtDataFig 5a-f.ipynb new file mode 100644 index 0000000..38a8655 --- /dev/null +++ b/Figure 3a-d, ExtDataFig 5a-f.ipynb @@ -0,0 +1,662 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from scipy.stats import ttest_ind\n", + "from scipy.stats import ttest_1samp" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "test = pd.read_pickle('data/SS3_c57_UMIs_mESC_vs_SS3_c57_UMIs_concat_TEST.pkl')\n", + "gene_annotation = pd.read_csv('data/mouse_gene_annotation.csv', index_col=0)\n", + "test.drop(gene_annotation['name2'][gene_annotation.chrom == 'chrX'].index.values, errors='ignore', inplace=True)\n", + "\n", + "bf_p = test[2][test[2] != 1][test[2] != 0]\n", + "bs_p = test[3][test[3] != 1][test[3] != 0]\n", + "\n", + "bf_mESC = pd.Series([gene[0] for gene in test[0]], index=test.index)\n", + "bf_Fib = pd.Series([gene[0] for gene in test[1]], index=test.index)\n", + "bs_mESC = pd.Series([gene[2]/gene[1] for gene in test[0]], index=test.index)\n", + "bs_Fib = pd.Series([gene[2]/gene[1] for gene in test[1]], index=test.index)\n", + "me_mESC = pd.Series([gene[2]*(gene[0]/(gene[1]+gene[0])) for gene in test[0]], index=test.index)\n", + "me_Fib = pd.Series([gene[2]*(gene[0]/(gene[1]+gene[0])) for gene in test[1]], index=test.index)\n", + "\n", + "bf_p = bf_p.dropna()\n", + "bs_p = bs_p.dropna()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1552\n", + "1075\n" + ] + } + ], + "source": [ + "from statsmodels.sandbox.stats.multicomp import multipletests\n", + "\n", + "bf_p_fdr = multipletests(bf_p, alpha=0.05, method='fdr_bh')\n", + "bs_p_fdr = multipletests(bs_p, alpha=0.05, method='fdr_bh')\n", + "print(np.sum(bf_p_fdr[0]))\n", + "print(np.sum(bs_p_fdr[0]))\n", + "bf_fdr_series = pd.Series(bf_p_fdr[0], index=bf_p.index)\n", + "bs_fdr_series = pd.Series(bs_p_fdr[0], index=bs_p.index)\n", + "bf_sig_names = bf_fdr_series.index.values[bf_fdr_series]\n", + "bs_sig_names = bs_fdr_series.index.values[bs_fdr_series]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Figure 2a-b" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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piIiI8PKNREREUFNTQ0dHB83Nrunu73//O62trQBERUWxcOFC4uPjcTgcRERE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\nTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(np.log10(bf_Fib), np.log10(bf_mESC), s = 1, color='Grey')\n", + "plt.scatter(np.log10(bf_Fib[bf_sig_names]), np.log10(bf_mESC[bf_sig_names]), s = 1, color='Red')\n", + "plt.xlabel('Fibr. Burst frequency (log$_{10}$)')\n", + "plt.ylabel('mESC Burst frequency (log$_{10}$)')\n", + "plt.savefig('figures/Fig3a.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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SZ3fjtm1j0qZNHfZTXFtLTkoK6bW1pCUnf7Odi5XK3r17KS0tBeDJJ590eyznmWRP76m7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eG3fj3V2dmEffghGbt3U56ZScwjj9Cck0NMWRl1u3eTvn07MWfOYImPp+azz8hcu5bi2lpOpqRQ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\nAc+akmYbp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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(np.log10(bs_Fib), np.log10(bs_mESC), s = 1, color='Grey')\n", + "plt.scatter(np.log10(bs_Fib[bs_sig_names]), np.log10(bs_mESC[bs_sig_names]), s = 1, color='Red')\n", + "plt.xlabel('Fibr. Burst size (log$_{10}$)')\n", + "plt.ylabel('mESC Burst size (log$_{10}$)')\n", + "plt.savefig('figures/Fig3b.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Figure 2C" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "rel_df = pd.DataFrame([np.log2(bf_mESC/bf_Fib),np.log2(bs_mESC/bs_Fib),np.log2(me_mESC/me_Fib)], index=['bf', 'bs', 'me'], columns=test.index).T\n", + "\n", + "rel_df = rel_df.sort_values('me')\n", + "rel_df = rel_df[np.absolute(rel_df['me']) < 5]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def bin_array(arr, l = 200):\n", + " binned_arr = np.array([])\n", + " bin_seq = np.array([])\n", + " for i in range(np.int_(np.floor(len(arr)/l))-1):\n", + " binned_arr = np.append(binned_arr, np.mean(arr[l*i:l*(i+1)]))\n", + " if i == np.int_(np.floor(len(arr)/l))-1:\n", + " bin_seq = np.append(bin_seq, arr[l*i])\n", + " bin_seq = np.append(bin_seq, arr[l*(i+1)])\n", + " else:\n", + " bin_seq = np.append(bin_seq, arr[l*i])\n", + " return binned_arr, bin_seq" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "n_bins = 50\n", + "rel_df['bin'] = pd.cut(rel_df['me'], n_bins, labels = [x for x in np.arange(n_bins)], right=True)\n", + "\n", + "rel_df_median = rel_df.groupby(by='bin').median()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Yt9hjwlcZtiJxEvXQmommPRCLUGp/GlAw44uIysnJ8dJMcnJytGYSZB+h3k8Uot/QDniN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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(1, 1)\n", + "rel_df.boxplot(column='bf', by='bin', grid = False, ax=ax, rot=45, positions=rel_df_median['me'])\n", + "plt.plot(rel_df_median['me'], rel_df_median['bf'])\n", + "#plt.plot(rel_df_median['me'], rel_df_median['bs'])\n", + "#rel_df.boxplot(column='bs', by='bin', grid = False, ax=ax, showfliers=False, rot=45, positions=rel_df_median['me'])\n", + "#ax.set_xticklabels(np.round(rel_df_median['me'],4))\n", + "ax.set_xticklabels('')\n", + "ax.set_title('')\n", + "ax.set_xlabel(r'Expression, mESC/Fib. ($log_2$)')\n", + "ax.set_ylabel(r' mESC/Fib. ($log_2$)')\n", + "#rel_df.boxplot(column='bs', by='bin', grid = False, ax=ax)\n", + "plt.savefig('figures/ExtDataFig5a.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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hZs6caXJycjoEJZY6xyMMU6ZMiVi+F8h0MfF6G6JikiK8EtHSFYhmn/eaGSAVS9ADZubM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\nPzhvLpSN+3zCAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(1, 1)\n", + "#rel_df.boxplot(column='bf', by='bin', grid = False, ax=ax, showfliers=False, rot=45, positions=rel_df_median['me'])\n", + "#plt.plot(rel_df_median['me'], rel_df_median['bf'])\n", + "plt.plot(rel_df_median['me'], rel_df_median['bs'])\n", + "rel_df.boxplot(column='bs', by='bin', grid = False, ax=ax, rot=45, positions=rel_df_median['me'])\n", + "#ax.set_xticklabels(np.round(rel_df_median['me'],4))\n", + "ax.set_xticklabels('')\n", + "ax.set_title('')\n", + "ax.set_xlabel(r'Expression, mESC/Fib. ($log_2$)')\n", + "ax.set_ylabel(r' mESC/Fib. ($log_2$)')\n", + "#rel_df.boxplot(column='bs', by='bin', grid = False, ax=ax)\n", + "plt.savefig('figures/ExtDataFig5b.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ttest_indResult(statistic=-24.629798597721454, pvalue=3.3859382029131138e-62)\n", + "Ttest_1sampResult(statistic=-15.378133968504098, pvalue=5.497594241157983e-28)\n", + "Ttest_1sampResult(statistic=20.874665464263998, pvalue=4.863197627378701e-38)\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "n = 100\n", + "rel_df = rel_df.sort_values('bf')\n", + "plt.boxplot([rel_df['me'][:n], rel_df['me'][-n:]], labels=['Top 100 fold change bf for Fibr.', 'Top 100 fold change bf mESC'])\n", + "plt.ylabel('Fold change mean expression (mESC/Fibr.)')\n", + "print(ttest_ind(rel_df['me'][:n], rel_df['me'][-n:]))\n", + "print(ttest_1samp(rel_df['me'][:n], 0))\n", + "print(ttest_1samp(rel_df['me'][-n:], 0))\n", + "plt.savefig('figures/ExtDataFig5c.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ttest_indResult(statistic=-5.284085553808783, pvalue=3.317987916286379e-07)\n", + "Ttest_1sampResult(statistic=-5.4942128257966765, pvalue=3.0501244850762615e-07)\n", + "Ttest_1sampResult(statistic=1.6644770143044012, pvalue=0.09917918508840574)\n" + ] + }, + { + "data": { + 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rel_df = rel_df.sort_values('bs')\n", + "plt.boxplot([rel_df['me'][:n], rel_df['me'][-n:]], labels=['Top 100 fold change bs for Fibr.', 'Top 100 fold change bs mESC'])\n", + "plt.ylabel('Fold change mean expression (mESC/Fibr.)')\n", + "print(ttest_ind(rel_df['me'][:n], rel_df['me'][-n:]))\n", + "print(ttest_1samp(rel_df['me'][:n], 0))\n", + "print(ttest_1samp(rel_df['me'][-n:], 0))\n", + "plt.savefig('figures/ExtDataFig5d.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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NbAYX/Xs9r6xL4MpxEXz/+2lMiQ529NA6prwk6B4JPcdA4Qkozmn6eq3NjD3qAnBxgTGL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\nv0HlHKHn/IeZGh3Cw1/s5du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C\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(rel_df_median['me'], rel_df_median['bf'])\n", + "plt.plot(rel_df_median['me'], rel_df_median['bs'])\n", + "plt.savefig('figures/Fig3c.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Figure 2D" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def convert_to_array(string):\n", + " return np.int_(list(filter(None, string.split(','))))" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def get_genes(EPU):\n", + " names = np.array([])\n", + " for tss in EPU:\n", + " names = np.append(TSS.loc[tss]['Gene'], names)\n", + " return np.unique(names)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def map_to_enhancer_manorm(gene, cell_type_fe):\n", + " enhancers = cell_type_fe[cell_type_fe['chr'] == gene['chr']]\n", + " w = np.array([gene['EPU start'] <= enh <= gene['EPU end'] for enh in enhancers['start']])\n", + " enhancers_in_epu = enhancers['M_value'][w]\n", + " return np.mean(enhancers_in_epu)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def log_enh(enh1,enh2):\n", + " if len(enh2) != 0 and len(enh1) != 0:\n", + " return np.log2(np.sum(enh1)/np.sum(enh2))\n", + " else:\n", + " return np.nan" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "EPU = pd.read_csv('data/EPUs.csv', header=0)\n", + "TSS = pd.read_csv('data/TSS_sites.csv', header=0)\n", + "\n", + "TSS.index = TSS['TSS']\n", + "\n", + "EPU['promoters inside the EPU'] = EPU['promoters inside the EPU'].apply(convert_to_array)\n", + "\n", + "EPU_plus_genes = pd.concat([EPU, EPU['promoters inside the EPU'].apply(get_genes)], axis = 1)\n", + "\n", + "EPU_plus_genes.columns = ['chr', 'EPU start', 'EPU end', 'promoters inside the EPU', 'genes inside the EPU']" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "MEF_fold_enrichment = pd.read_csv('data/MEF_peaks.xls', skiprows=23, sep='\\t')\n", + "mESC_fold_enrichment = pd.read_csv('data/mESC_peaks.xls', skiprows=23, sep='\\t')\n", + "\n", + "manorm_fold_enrichment = pd.read_csv('data/manorm_MEF_mESC_all_MAvalues.xls', sep='\\t')" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Parallel(n_jobs=50)]: Done 28 tasks | elapsed: 1.3s\n", + "[Parallel(n_jobs=50)]: Done 188 tasks | elapsed: 6.6s\n", + "[Parallel(n_jobs=50)]: Done 412 tasks | elapsed: 13.8s\n", + "[Parallel(n_jobs=50)]: Done 700 tasks | elapsed: 22.8s\n", + "[Parallel(n_jobs=50)]: Done 1052 tasks | elapsed: 34.1s\n", + "[Parallel(n_jobs=50)]: Done 1468 tasks | elapsed: 46.7s\n", + "[Parallel(n_jobs=50)]: Done 1948 tasks | elapsed: 1.1min\n", + "[Parallel(n_jobs=50)]: Done 2492 tasks | elapsed: 1.4min\n", + "[Parallel(n_jobs=50)]: Done 3100 tasks | elapsed: 1.7min\n", + "[Parallel(n_jobs=50)]: Done 3772 tasks | elapsed: 2.1min\n", + "[Parallel(n_jobs=50)]: Done 4508 tasks | elapsed: 2.5min\n", + "[Parallel(n_jobs=50)]: Done 5308 tasks | elapsed: 2.8min\n", + "[Parallel(n_jobs=50)]: Done 6172 tasks | elapsed: 3.1min\n", + "[Parallel(n_jobs=50)]: Done 7100 tasks | elapsed: 3.4min\n", + "[Parallel(n_jobs=50)]: Done 8092 tasks | elapsed: 3.8min\n", + "[Parallel(n_jobs=50)]: Done 8792 out of 8792 | elapsed: 4.2min finished\n" + ] + } + ], + "source": [ + "from joblib import delayed, Parallel\n", + "enh_MEF = Parallel(n_jobs=50, verbose=3)(delayed(map_to_enhancer_manorm)(epu, manorm_fold_enrichment) for i,epu in EPU_plus_genes.iterrows())" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "EPU_plus_genes['enh_manorm'] = enh_MEF" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "gene_name = []\n", + "log_enh_list = []\n", + "for i,row in EPU_plus_genes.iterrows():\n", + " g_inside = row['genes inside the EPU']\n", + " l_enh = row['enh_manorm']\n", + " gene_name.extend(g_inside)\n", + " log_enh_list.extend(np.repeat(l_enh, len(g_inside)))" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "log_enh_series = pd.Series(log_enh_list, index=gene_name).dropna()\n", + "\n", + "log_enh_series = log_enh_series[~log_enh_series.index.duplicated(keep='first')]\n", + "\n", + "enh_df = pd.DataFrame([np.log2(bf_mESC/bf_Fib),np.log2(bs_mESC/bs_Fib), -log_enh_series], index=['bf', 'bs', 'enh']).T.dropna(how='any')\n", + "\n", + "enh_df['enh'] = enh_df['enh'] - np.mean(enh_df['enh'])" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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X3W7aaR0MS/QeJupwutj/cYcYt2aLyVd4tqv3tpk3wNSrfI/Pudn8dCwl6eC9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\n/wPKZXYuT/dAVgAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "enh_df = enh_df.sort_values('bf')\n", + "rolling_bf = enh_df.rolling(200).mean().dropna()\n", + "plt.plot(rolling_bf['bf'], rolling_bf['enh'], label='BF')\n", + "enh_df = enh_df.sort_values('bs')\n", + "rolling_bs = enh_df.rolling(200).mean().dropna()\n", + "plt.plot(rolling_bs['bs'], rolling_bs['enh'],alpha=0.4, label='BS')\n", + "plt.legend()\n", + "plt.savefig('figures/Fig3d.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ttest_indResult(statistic=-11.401588799591433, pvalue=1.776718669215198e-23)\n", + "Ttest_1sampResult(statistic=-8.801852050527312, pvalue=4.4655256091184455e-14)\n", + "Ttest_1sampResult(statistic=7.260607917846643, pvalue=8.864615267037344e-11)\n" + ] + }, + { + "data": { + "image/png": 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RrpmZjUSehLBJUgvZ+EVImkWOYbAj4vB68yWdBBwFvCcios56VgIrAVpbWwddzszMGpOn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\nJU4IZmYGwP8H42B958SYvHcAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "n = 100\n", + "enh_df = enh_df.sort_values('bf')\n", + "plt.boxplot([enh_df['enh'][:n], enh_df['enh'][-n:]], labels=['Top 100 fold change bf for Fibr.', 'Top 100 fold change bf mESC'])\n", + "plt.ylabel('Enhancer magnitude (mESC/Fibr.)')\n", + "print(ttest_ind(enh_df['enh'][:n], enh_df['enh'][-n:]))\n", + "print(ttest_1samp(enh_df['enh'][:n], 0))\n", + "print(ttest_1samp(enh_df['enh'][-n:], 0))\n", + "plt.savefig('figures/ExtDataFig5e.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ttest_indResult(statistic=-1.804977940350096, pvalue=0.0725974269409498)\n", + "Ttest_1sampResult(statistic=-2.7157137557541646, pvalue=0.0078049233408416865)\n", + "Ttest_1sampResult(statistic=-0.20598405788940996, pvalue=0.8372263631661159)\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "enh_df = enh_df.sort_values('bs')\n", + "plt.boxplot([enh_df['enh'][:n], enh_df['enh'][-n:]], labels=['Top 100 fold change bs for Fibr.', 'Top 100 fold change bs mESC'])\n", + "plt.ylabel('Enhancer magnitude (mESC/Fibr.)')\n", + "print(ttest_ind(enh_df['enh'][:n], enh_df['enh'][-n:]))\n", + "print(ttest_1samp(enh_df['enh'][:n], 0))\n", + "print(ttest_1samp(enh_df['enh'][-n:], 0))\n", + "plt.savefig('figures/ExtDataFig5f.pdf')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Figure 3e, ExtDataFig 7a-f.ipynb b/Figure 3e, ExtDataFig 7a-f.ipynb new file mode 100644 index 0000000..4bd6098 --- /dev/null +++ b/Figure 3e, ExtDataFig 7a-f.ipynb @@ -0,0 +1,382 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n" + ] + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import sys\n", + "import pandas as pd\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import matplotlib.colors as colors\n", + "# set the colormap and centre the colorbar\n", + "class MidpointNormalize(colors.Normalize):\n", + "\t\"\"\"\n", + "\tNormalise the colorbar so that diverging bars work there way either side from a prescribed midpoint value)\n", + "\n", + "\te.g. im=ax1.imshow(array, norm=MidpointNormalize(midpoint=0.,vmin=-100, vmax=100))\n", + "\t\"\"\"\n", + "\tdef __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):\n", + "\t\tself.midpoint = midpoint\n", + "\t\tcolors.Normalize.__init__(self, vmin, vmax, clip)\n", + "\n", + "\tdef __call__(self, value, clip=None):\n", + "\t\t# I'm ignoring masked values and all kinds of edge cases to make a\n", + "\t\t# simple example...\n", + "\t\tx, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]\n", + "\t\treturn np.ma.masked_array(np.interp(value, x, y), np.isnan(value))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "data = pd.read_csv('data/data_new_june28.tab', sep='\\t' ,index_col=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "fc_bf = []\n", + "fc_bs = []\n", + "bfpval = []\n", + "bspval = []\n", + "gene_list = []\n", + "method_list = []\n", + "for gene in data.index.unique():\n", + " df = data.loc[gene]\n", + " for m in df['method'].unique():\n", + " df_m = df[df['method'] == m]\n", + " es = df_m[df_m['celltype'] == 'es']\n", + " fib = df_m[df_m['celltype'] == 'fib']\n", + " gene_list.append(gene)\n", + " method_list.append(m)\n", + " fc_bf.append(np.log10(es['kon']/fib['kon']))\n", + " fc_bs.append(np.log10((es['ksyn']/es['koff'])/(fib['ksyn']/fib['koff'])))\n", + " bfpval.append(np.log10(es['bfpval']))\n", + " bspval.append(np.log10(es['bspval']))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "heatmap_fc = np.array([])\n", + "for bf, bs in zip(np.array(fc_bf).reshape(4,2), np.array(fc_bs).reshape(4,2)):\n", + " heatmap_fc = np.concatenate((heatmap_fc, bf))\n", + " heatmap_fc = np.concatenate((heatmap_fc, bs))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "param_list = ['bf' if i % 2 == 0 else 'bs' for i in np.arange(8) ]" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "elev_min = min(heatmap_fc)\n", + "elev_max = max(heatmap_fc)\n", + "mid_val = 0\n", + "plt.imshow(heatmap_fc.reshape(8,2), cmap='RdBu', clim=(elev_min, elev_max), norm=MidpointNormalize(midpoint=mid_val,vmin=elev_min, vmax=elev_max))\n", + "plt.yticks(np.arange(8), ['{} {}'.format(g,m) for g,m in zip(gene_list,param_list)])\n", + "plt.title('Fold change log$_{10}$(mESC/Fibr.)')\n", + "plt.xticks(np.arange(2), ['scRNA', 'smFISH'], rotation=45, ha='right')\n", + "plt.colorbar()\n", + "plt.tight_layout()\n", + "plt.savefig('figures/Fig3e_burst_kinetics.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "heatmap_p = np.array([])\n", + "for bf, bs in zip(np.array(bfpval).reshape(4,2), np.array(bspval).reshape(4,2)):\n", + " heatmap_p = np.concatenate((heatmap_p, bf))\n", + " heatmap_p = np.concatenate((heatmap_p, bs))" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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3UgPeaSG7N4D7zOz2+GJ3gKSNCdVxJxGq5hYnxNB/MLNckzU6+eiLXnOSxhJK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\nHVzMTs/gYnZ6Bhez0zO4mJ2e4f8DazW5tI7b7y4AAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(heatmap_p.reshape(8,2), cmap='Greens_r')\n", + "plt.yticks(np.arange(8), ['{} {}'.format(g,m) for g,m in zip(gene_list,param_list)])\n", + "plt.title('Significance log$_{10}$(p-value)')\n", + "plt.xticks(np.arange(2),['scRNA', 'smFISH'], rotation=45, ha='right')\n", + "plt.colorbar()\n", + "plt.tight_layout()\n", + "plt.savefig('figures/Fig3e_significance.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# simple test, drawing RNA copies per cell distributions for selected parameters\n", + "def plotHist(vals, g, typ):\n", + " plt.figure(figsize=(4,4))\n", + " plt.hist(vals, bins=10)\n", + " plt.title('{} {}'.format(g, typ))\n", + " plt.xlabel(\"RNA copies per cell\")\n", + " plt.ylabel(\"Number of observations\")\n", + " plt.savefig('figures/ExtDataFig7a_d_scRNA_{}_{}_hist.pdf'.format(typ, g))\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "fib = pd.read_csv('data/SS3_active_X_UMI.csv', index_col=0)\n", + "es = pd.read_csv('data/SS3_c57_UMIs_mESC.csv', index_col=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for gene in data.index.unique():\n", + " plotHist(fib.loc[gene][pd.notnull(fib.loc[gene])], gene, 'fib')\n", + " plotHist(es.loc[gene][pd.notnull(es.loc[gene])], gene, 'es')" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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C1atX19q1a4dWpyQtRUluqKrVM+036ruG7kuyK0Dz8/4Rn1+SNMmog+BS4Lhm+TjgkhGf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\nSeo4g0CSOs4gkKSOMwgkqeP+PxCObvWAy9TzAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(data[data['method'] == 'scRNA']['ksyn']/data[data['method'] == 'scRNA']['koff'], data[data['method'] == 'fish']['ksyn']/data[data['method'] == 'fish']['koff'])\n", + "plt.xlabel('Burst size scRNA')\n", + "plt.ylabel('Burst size smFISH')\n", + "plt.xlim((0,15))\n", + "plt.ylim((0,55))\n", + "plt.savefig('figures/ExtDataFig7e.pdf')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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NTHmuHD5DMujdoZK6gd+SPAhnZmYjVN3kIGkXoDMi3iPpNcAuEfF8c0IzM7Oy1L2tFBGv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\nyYRIfx0Rp6TbV+7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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(data[data['method'] == 'scRNA']['kon'], data[data['method'] == 'fish']['kon'])\n", + "plt.xlabel('Burst frequency scRNA')\n", + "plt.ylabel('Burst frequency smFISH')\n", + "plt.savefig('figures/ExtDataFig7f.pdf')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Figure 4a-c, ExtDataFig 8a-d, 5g.ipynb b/Figure 4a-c, ExtDataFig 8a-d, 5g.ipynb new file mode 100644 index 0000000..dd7f0df --- /dev/null +++ b/Figure 4a-c, ExtDataFig 8a-d, 5g.ipynb @@ -0,0 +1,457 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n", + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility. Expected 96, got 88\n", + " return f(*args, **kwds)\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from statsmodels.sandbox.stats.multicomp import multipletests" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "307\n", + "276\n" + ] + } + ], + "source": [ + "test = pd.read_pickle('data/SS3_c57_UMIs_concat_vs_SS3_cast_UMIs_concat_TEST.pkl')\n", + "gene_annotation = pd.read_csv('data/mouse_gene_annotation.csv', index_col=0)\n", + "test.drop(gene_annotation['name2'][gene_annotation.chrom == 'chrX'].index.values, errors='ignore', inplace=True)\n", + "\n", + "bf_p = test[2]\n", + "bs_p = test[3]\n", + "\n", + "bf_c57 = pd.Series([gene[0] for gene in test[0]], index=test.index)\n", + "bf_cast = pd.Series([gene[0] for gene in test[1]], index=test.index)\n", + "bs_c57 = pd.Series([gene[2]/gene[1] for gene in test[0]], index=test.index)\n", + "bs_cast = pd.Series([gene[2]/gene[1] for gene in test[1]], index=test.index)\n", + "\n", + "bf_p = bf_p.dropna()\n", + "bs_p = bs_p.dropna()\n", + "\n", + "bf_p_fdr = multipletests(bf_p, alpha=0.05, method='fdr_bh')\n", + "bs_p_fdr = multipletests(bs_p, alpha=0.05, method='fdr_bh')\n", + "print(np.sum(bf_p_fdr[0]))\n", + "print(np.sum(bs_p_fdr[0]))\n", + "bf_fdr_series = pd.Series(bf_p_fdr[0], index=bf_p.index)\n", + "bs_fdr_series = pd.Series(bs_p_fdr[0], index=bs_p.index)\n", + "bf_sig_names = bf_fdr_series.index.values[bf_fdr_series]\n", + "bs_sig_names = bs_fdr_series.index.values[bs_fdr_series]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Ocs+eZe5TTw37nta77uJgRwcOhwNDYCCr3nuPA+Hh7L32WmJjY+ns7MTPz4+B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\nCR0AAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(np.log10(bf_c57), np.log10(bf_cast), s = 1, color='Grey')\n", + "plt.scatter(np.log10(bf_c57[bf_sig_names]), np.log10(bf_cast[bf_sig_names]), s = 1, color='Red')\n", + "plt.xlabel('Burst frequency C57 (log$_{10}$)')\n", + "plt.ylabel('Burst frequency CAST (log$_{10}$)')\n", + "plt.savefig('figures/Fig4a.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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7yO12660pel5+mareXqrmzYOAwTlDod3vW7duUfblL5Obm8vHH3+sz4SumjcP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\n6NfTSCnlV0CYE38ggXfeu4yoqCjq6+t7pPyora2lra2NuLi4XjsSpRS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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(np.log10(bs_c57), np.log10(bs_cast), s = 1, color='Grey')\n", + "plt.scatter(np.log10(bs_c57[bs_sig_names]), np.log10(bs_cast[bs_sig_names]), s = 1, color='Red')\n", + "plt.xlabel('Burst size C57 (log$_{10}$)')\n", + "plt.ylabel('Burst size CAST (log$_{10}$)')\n", + "plt.savefig('figures/Fig4b.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "def read_variation_bed(file):\n", + " bed_file = pd.read_csv(file, delimiter=\"\\t\", header = None, index_col=3)\n", + " return bed_file" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "SNPs = read_variation_bed('data/every_snp_enhancers_per.bed')\n", + "SNPs['name'] = SNPs.index.values" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/mnt/kauffman/nbserver/jupyter-run-software/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:6: FutureWarning: \n", + "Passing list-likes to .loc or [] with any missing label will raise\n", + "KeyError in the future, you can use .reindex() as an alternative.\n", + "\n", + "See the documentation here:\n", + "https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike\n", + " \n" + ] + } + ], + "source": [ + "log_diff_bf = pd.Series(np.absolute(np.log(bf_c57/bf_cast)), index=bf_c57.index).sort_values()\n", + "log_diff_bs = pd.Series(np.absolute(np.log(bs_c57/bs_cast)), index=bs_c57.index).sort_values()\n", + "\n", + "sig_bf_fc = log_diff_bf[bf_sig_names].sort_values()\n", + "sig_bs_fc = log_diff_bs[bs_sig_names].sort_values()\n", + "Y=SNPs.loc[bf_p.sort_values().index].dropna().groupby('name').size()[bf_p.sort_values().index].dropna()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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51z/Dh+PPV6aNL2z34hgk2rGWoESZ85d/ZvOUWcxZtCT/RUUSCYfw3/svHJBW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\n/swhPlUlHK1sLT4vpplnQ3D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DdgM3isixOHurrlDV3hLmzMmd6+8ccWxB+wIWT1pMOBbm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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(np.log10(bf_p.sort_values()[Y[bf_p.sort_values().index].dropna().index].rolling(50).median().dropna()), np.array(Y[bf_p.sort_values().index].dropna().rolling(50).median().dropna()))\n", + "plt.plot(np.log10(bf_p.sort_values()[Y[bf_p[sig_bf_fc.index].sort_values().index].dropna().index].rolling(50).median().dropna()), np.array(Y[bf_p[sig_bf_fc.index].sort_values().index].dropna().rolling(50).median().dropna()))\n", + "plt.plot([-7,0],[6,6], '--', alpha=0.5)\n", + "plt.xlabel('Rolling median p-value burst frequency ($log_{10}$)')\n", + "plt.ylabel('Rolling median number of strain \\n specific mutations in enhancer regions')\n", + "plt.tight_layout()\n", + "plt.savefig('figures/Fig4c.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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KS0ubb5sWY0FNWxp/Dap2YwVRUEKmokmSv45Wm6r+S1lSGQxTGIkNMiTttORpY0fxGQU1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\nlZITlJmZlZITlJmZldL/A8MdcqiR5Rs6AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(np.log10(bs_p.sort_values()[Y[bs_p.sort_values().index].dropna().index].rolling(50).median().dropna()), np.array(Y[bs_p.sort_values().index].dropna().rolling(50).median().dropna()))\n", + "plt.plot(np.log10(bs_p.sort_values()[Y[bs_p[sig_bs_fc.index].sort_values().index].dropna().index].rolling(50).median().dropna()), np.array(Y[bs_p[sig_bs_fc.index].sort_values().index].dropna().rolling(50).median().dropna()))\n", + "plt.plot([-5.5,0],[6,6], '--', alpha=0.5)\n", + "plt.xlabel('Rolling median p-value burst size ($log_{10}$)')\n", + "plt.ylabel('Rolling median number of strain \\n specific mutations in enhancer regions')\n", + "plt.tight_layout()\n", + "plt.savefig('figures/ExtDataFig5g.pdf')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "bf_cast_example = ['Sept8', 'Scp2', 'Car13']\n", + "bf_c57_example = ['Ccbe1', 'Arhgef5', 'Srf']\n", + "bs_c57_example = ['Phgdh','Snx7', 'Zyx']\n", + "bs_cast_example = ['Cdc42se1', 'Ndrg1', 'Ctsf']" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "c57_UMI = pd.read_csv('data/SS3_c57_UMIs_concat.csv', index_col=0)\n", + "cast_UMI = pd.read_csv('data/SS3_cast_UMIs_concat.csv', index_col=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for gen in bf_cast_example:\n", + " name = gen\n", + " plt.title(name)\n", + " plt.hist(cast_UMI.loc[name][pd.notnull(cast_UMI.loc[name])], bins = 20, label='cast', alpha=0.5)\n", + " plt.hist(c57_UMI.loc[name][pd.notnull(c57_UMI.loc[name])], bins = 20, label='c57', alpha=0.5)\n", + " plt.legend()\n", + " plt.savefig('figures/ExtDataFig8a_{}_bf_upin_cast.pdf'.format(gen))\n", + " plt.show()\n", + "for gen in bf_c57_example:\n", + " name = gen\n", + " plt.title(name)\n", + " plt.hist(cast_UMI.loc[name][pd.notnull(cast_UMI.loc[name])], bins = 20, label='cast', alpha=0.5)\n", + " plt.hist(c57_UMI.loc[name][pd.notnull(c57_UMI.loc[name])], bins = 20, label='c57', alpha=0.5)\n", + " plt.legend()\n", + " plt.savefig('figures/ExtDataFig8b_{}_bf_upin_c57.pdf'.format(gen))\n", + " plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for gen in bs_cast_example:\n", + " name = gen\n", + " plt.title(name)\n", + " plt.hist(cast_UMI.loc[name][pd.notnull(cast_UMI.loc[name])], bins = 20, label='cast', alpha=0.5)\n", + " plt.hist(c57_UMI.loc[name][pd.notnull(c57_UMI.loc[name])], bins = 20, label='c57', alpha=0.5)\n", + " plt.legend()\n", + " plt.savefig('figures/ExtDataFig8c_{}_bs_upin_cast.pdf'.format(gen))\n", + " plt.show()\n", + "for gen in bs_c57_example:\n", + " name = gen\n", + " plt.title(name)\n", + " plt.hist(cast_UMI.loc[name][pd.notnull(cast_UMI.loc[name])], bins = 20, label='cast', alpha=0.5)\n", + " plt.hist(c57_UMI.loc[name][pd.notnull(c57_UMI.loc[name])], bins = 20, label='c57', alpha=0.5)\n", + " plt.legend()\n", + " plt.savefig('figures/ExtDataFig8d_{}_bs_upin_c57.pdf'.format(gen))\n", + " plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}