graph-ISS

Graph-based Decoding for In Situ Sequencing (ISS).

This repository contains the primary source code implementation of the graph-based image analysis pipeline for processing in situ sequencing data and ipython notebooks for reproducing publication analysis results and figures [ref]. The image decoding pipeline consists in three Python 3 library packages for 2D and 3D data proccesing and a Anduril2 [2] pipeline implementing the decoding workflow.

[2] Cervera, Alejandra, et al. "Anduril 2: upgraded large-scale data integration framework." Bioinformatics (2019).

Decoding Pipeline Install Requirements

Anduril2

Anduril 2 is a workflow platform for high-throughput analysis of biomedical data. Workflows are constructed using Scala 2.11 and executed in parallel locally or on Linux clusters using a workflow engine optimized for iterative development. Documentation and installation instructions are available at: http://anduril.org.

Bio-Format Command Line Tools

Bio-format command line tools are necessary for dividing whole slide images in smaller tiles for faster computation. Bio-format command line tools can be downloaded from https://www.openmicroscopy.org/bio-formats.

Python Library Requirements

Create a conda evironment named "pgm_pipeline":

$ conda create --name pgm_pipeline

Activate environment:

$ conda activate pgm_pipeline

Install the following python packages:

• joblib>=0.13.2
• keras>=2.2.4
• networkx>=2.3
• numpy>=1.13.1
• pandas>=0.23.4
• scikit-image>=0.13.0
• scikit-learn>=0.21.3
• scipy>=0.19.1
• pytables>=3.4.2
• tqdm>=4.32.2

Install SimpleElastix inside the virtual environment following installation instructions and documentation available at https://simpleelastix.readthedocs.io.

To deactivate the conda enviroment:

$ conda deactivate

Analysis Notebook Install Requirements

The following python packages are required for running the notebooks:

• joblib>=0.13.2
• matplotlib>=2.2.2
• networkx>=2.3
• nimfa>=1.3.4
• numpy>=1.13.1
• opencv-python>=3.4.1.15
• pandas>=0.23.4
• scikit-image>=0.13.0
• scikit-learn>=0.21.3
• scipy>=0.19.1
• seaborn>=0.9.0
• SpatialDE>=1.1.3
• tqdm>=4.32.2
• umap-learn>=0.3.9

Data Download

An example ISS data [3] for testing Anduril decoding pipeline and decoding results for reproducing publication analyses can be downloaded from: https://doi.org/10.5281/zenodo.3357950.

[3] Ke, Rongqin, et al. "In situ sequencing for RNA analysis in preserved tissue and cells." Nature methods 10.9 (2013): 857.

Anduril Pipeline Example Usage

An example of 2D Anduril decoding pipeline is availabel for testing (ISS_Anduril_Pipeline_Example.scala). For running the test example, <GRAPH-ISS-FOLDER> and <DATA-FOLDER> strings in the scala file should be replaced respectively with graph-iss and downloaded data folder local paths.

To lunch the execution, run the command:

$ ./ISS_Anduril_Pipeline_Example.scala