Meta-analysis of crowdsourced data compendia suggests pan-disease transcriptional signatures of autoimmunity.

ABSTRACT: Background: The proliferation of publicly accessible large-scale biological data together with increasing availability of bioinformatics tools have the potential to transform biomedical research. Here we report a crowdsourcing Jamboree that explored whether a team of volunteer biologists without formal bioinformatics training could use OMiCC, a crowdsourcing web platform that facilitates the reuse and (meta-) analysis of public gene expression data, to compile and annotate gene expression data, and design comparisons between disease and control sample groups. Methods: The Jamboree focused on several common human autoimmune diseases, including systemic lupus erythematosus (SLE), multiple sclerosis (MS), type I diabetes (DM1), and rheumatoid arthritis (RA), and the correspondin

SUBMITTER: Lau WW 

PROVIDER: S-EPMC5399965 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature