sgosline/dten repository overview

⁠Drug Target Expression Networks

A suite of tools designed to enable identification of drugs effective in a disease of interest based on gene expression data.

⁠Related Packages

Many packages are used by this workflow to enable proper assessment of the gene expressiond ata.

• MetaViper⁠: MetaViper is used to identify proteins of activity from gene expression data
• Drug Target Explorer⁠: DTEx is used to identify protein-drug interactions
• PCSF⁠: Prize-collecting steiner forest package is used for network reduction and pathway enrichment

⁠Using DTEN

The DTEN scientific workflow comprises a series of steps that can be performed individually or in sequence.

⁠Formatted Data

We have built another workflow that aligns and annotates fastq files and uploads them to Synapse. TODO: create workflow that combines aligned counts into tidieid data frame

⁠Getting Proteins of interest

DTEN assumes that files are in a tidied data frame with the following headers:

⁠Building networks and getting pathway enrichment

Once we have the proteins we can add them to networks

⁠Storing results on Synapse

⁠Selecting drugs and pathways across conditions

⁠Getting started

1. Install Docker
2. Install cwltool
3. Format your inputs in JSON format
4. cwl-runner workflow-name.cwl `inputfile.json'