Code and results for WQE, using WGCNA analyzing proteomics data This project aims to create a workflow for analyzing proteomics data through differential expression analysis and WGCNA to prioritize proteins that of interest based on experiment condition. It also includes modules for functional annotation and comparison for results coming from different analysis.
/prepocess Preprocess code for missing data imputation, data transformation
/WGCNA code for WGCNA analysis, including module traits association, connectivity calculation and so on
/Reactome code for Reactome parent pathway identification
/DisGeNet code for retrieve disease protein association from DisGeNet API
/ID_convertion code for project human protein to mouse protein or vice versa
/Differential_expression_analysis list of proteins with significant change, all proteins stats test results
/WGCNA module found by WGCNA and hub proteins of yellow module
/CaseOLAP top proteins identified by CaseOLAP
/Reactome Reactome results
/GeneOntology Gene ontology results
/Clinical Results of differentially expressed proteins identified in cinical study