Updated Readme and documention.tex to consider the chromatin conforma…

…tion capture data

README.md

@@ -1,4 +1,4 @@
-# TEPIC (version 2.1)
+#TEPIC (version 2.2)
 -------
 TEPIC offers workflows for the prediction and analysis of Transcription Factor (TF) binding sites including:
 * TF affinity computation in user provided regions
@@ -10,6 +10,8 @@ A graphical overview on the workflows of TEPIC is shown below. Blue font indicat
 ![](docs/TEPIC_Workflow.png)
 
 ## News
+08.10.2019: We present a novel feature to include TFBS in regulatory sites determined by chromatin conformation capture data. Using an extended feature space representation, the INVOKE model can investigate the regulatory influence of TFs bound to promoters and enhancers separately.
+
 10.10.2018: TEPIC 2.0 is now published in [Bioinformatics](https://doi.org/10.1093/bioinformatics/bty856).
 
 13.08.2018: In addition to the gene-centric annotation, the functionality for transcript based annotation has been added.
@@ -156,6 +158,11 @@ Here, thresholded TF affinities are used for the computation.
 	GENEID		TF1	TF2	...	TFn	peak length	peak count	peak signal
 	ENSG00000044612	0	0	...	4.2	23		3		19.2
 
+The *Prefix_Conformation_Data_Affinity_Three_Peak_Based_Features_Gene_View.txt* files are based on the previous structure but extend it by including the same features, that is TF gene-scores and peak features determined for DHS residing in chromatin loops:
+
+	GENEID		TF1	TF2	...	TFn	peak length	peak count	peak signal	LR_TF1	...	LR_TFn	LR_peak length	LR_peak count	LR_peak signal
+	ENSG00000044612	0	0	...	4.2	23		3		19.2		3.4	...	0.9	14	4	63.3
+
 The *Prefix_Thresholded_Sparse_Affinity_Gene_View.txt* files are tab separated files listing the Ensemble GeneID in the first column, and the name of the TF associated to this gene in the second column.
 Here, thresholded TF affinities are used for the computation. The third column of this file is required by DREM and does not carry any specific meaning.
 

docs/Description.tex

@@ -21,6 +21,7 @@
 \item Annotation of user defined regions with TF affinities using TRAP and a variety of provided TF-motifs,
 \item Aggregation of TF affinities to TF-gene scores,
 \item Computation of statistical scores such as peak-length, peak-count or peak-signal per gene,
+\item Inclusion of long range chromatin contacts,
 \item Discretization of continuous TF affinities using a background distribution into a binary measure for TF-binding,
 \item Linear regression analysis to infer key transcriptional regulators within one sample,
 \item Logistic regression classifier to suggest key transcriptional regulators between samples,
@@ -198,7 +199,6 @@ \subsection{Computing TF gene scores}
 
 Furthermore, TEPIC can compute a TF-specific affinity cut-off derived from either user-defined, or randomly generated sequences, to distinguish likely bound sites from unbound sites. These scores
 can be used to come-up with a binary TF-gene assignment. Further details on this mode are provided in Section \ref{EPIC-DREM}.
-
 \begin{figure}[h!]
 \begin{center}
 \includegraphics[width=\textwidth]{Workflow.png}
@@ -211,8 +211,18 @@ \subsection{Computing TF gene scores}
 \label{workflowFig}
 \end{figure}
 
+With version $2.2$ of TEPIC, we introduced support for the inclusion of long range chromatin conformation capture data. In addition to the promoter centric windows used before, we
+calculate TF affinities $a_{g,i}*$ and peak scores $pl_g*, pc_g*, ps_g*$ for all DHSs residing  in genomic loci looping into the promoter region of a gene, summarizied in $P_{g,V_g}$, where $V_g$ is the set of all regions looped into the promoter region of gene $g$:
+\begin{align}
+a_{g,i}&=\sum_{p \in P_{g,V_g}} a_{p,i},\\
+pl_g*&=\sum_{p \in P_{g,V_g}}|p|, \\
+pc_g*&=\sum_{p \in P_{g,V_g}}, \\
+ps_g*&=\sum_{p \in P_{g,V_g}}s_{p}.
+\end{align}
+Note that scores computed for $p \in P_{g,V_g}g$ are never considering the exponential decay as a direct interaction of the respective sites with the promoter region of gene $g$ has been determined by chromatin conformation capture experiments.
+
 \subsection{Required input}
-To compute TF gene scores a user needs to specify:
+To compute TF gene scores, a user needs to specify:
 \begin{itemize}
 \item a reference genome (-g option),
 \item a set of \textit{PSEMs} (-p option),