Chunk #5 — ENHANCEMENTS AND UPDATES — New gene set libraries — Differentially expressed genes after drug, gene, disease, ligand and pathogen perturbations extracted from GEO by the crowd
To extract gene sets from gene expression data deposited in the GEO (29), we established a crowdsourcing microtask project that asks participants to extract gene sets from GEO for the following categories: (1) single-gene perturbations in mammalian cells; (2) comparison of diseased versus normal tissues; (3) single-drug perturbations in mammalian cells; (4) perturbations applied to MCF7 cells; (5) comparison between young and old mammalian tissues; (6) endogenous ligand perturbations of mammalian cells; and (7) comparison of before and after pathogen infection of human cells. Participants of the microtasks were recruited via two Coursera massive online open courses (MOOCs) and worked voluntarily on finding relevant studies from the GEO database. Participants were instructed to identify control and perturbation samples (GSM files), and to add additional metadata such as cell-line/tissue used in each study, as well as IDs for genes, diseases and small molecules. Participants were also instructed to use the browser extension GEO2Enrichr (30) to extract differentially expressed gene sets from GEO. The metadata and gene sets were submitted to our crowdsourcing database and then converted to gene set libraries for Enrichr.
