Skip to content
set of scripts for calculating mutual ranks for all gene pairs in a dataset and calling coexpressed gene modules
Branch: master
Clone or download
Latest commit 73fca14 Sep 27, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
scripts fork module script Sep 27, 2019
tutorial fork module script Sep 27, 2019
README.md add link to website Sep 25, 2019

README.md

Mutual Ranks and Modules

Jen Wisecaver

2019-09-25

Set of scripts to identify co-expressed gene sets (i.e., modules) in gene co-expression networks.

Transforming Pearson’s correlation coefficents (PCCs) into Mutual Ranks (MRs) — first described by Obayashi & Kinoshita — is a good idea if you want to compare between different datasets and/or functional categories (Obayashi et al, 2018; Liesecke et al, 2018). However, the transformation requires significant memory and disk space to compute. Moreover, MRs range from 1 to n-1 (where n is the number of genes in the genome), which does not translate well to network edge weights. We’ve implemented a series of R and Python scripts for creating MRs and gene modules directly from a directory of Kallisto gene abundance estimates. The code as been developed to run on multiple threads when possible, which significantly decreasing the total runtime. Finally, the pipeline applies exponential decay functions to transform MRs into edge weights and call co-expressed gene sets (i.e. modules) using the program ClusterONE.

See Wisecaver et al. 2017 Plant Cell | PDF

Steps

An in depth tutorial is provided and includes information on files types, run time, memory requirements, etc. The TL:DR steps are provided below.

  1. Create a gene expression matrix
Rscript ../scripts/transform_counts.r -a example/abundance_files.txt -l example/transcripts2genes.txt -s example/sample_conditions.txt -t tag -o example/gene_counts 
  1. Calculate PCC and MR for all gene pairs
python ../scripts/calc_mr_pcc.py -i example/gene_counts_normalized.matrix -o example/gene_counts_normalized_mr -t 20
  1. Run clusterONE and call co-expressed gene modules
python ../scripts/create_network_and_modules.py -i example/gene_counts_normalized_mr -c ../scripts/cluster_one-1.0.jar -d 5
You can’t perform that action at this time.