Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd
Name
Extraction and analysis.pdf
Size
1.44 MB
Format
Adobe PDF
Checksum (MD5)
b4b52782354e05f775b7c47f64631058
Author(s)
Szeto, Gregory
Date Issued
September 2016
Journal
Nature Communications
Publisher
Nature Publishing Group
Citation
Wang, Zichen et al. “Extraction and Analysis of Signatures from the Gene Expression Omnibus by the Crowd.” Nature Communications 7 (2016): 12846.
Version
Final published version
Abstract
Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Ragon Institute of MGH, MIT and Harvard
Koch Institute for Integrative Cancer Research at MIT
Terms of Use
Creative Commons Attribution 4.0 International License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1038/ncomms12846
