Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd
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 expre...
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| Format: | Article |
| Language: | en_US |
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Nature Publishing Group
2017
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| Online Access: | http://hdl.handle.net/1721.1/107686 https://orcid.org/0000-0001-7604-1333 |
| _version_ | 1826206119557595136 |
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| author | Szeto, Gregory |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Szeto, Gregory |
| author_sort | Szeto, Gregory |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T13:24:24Z |
| format | Article |
| id | mit-1721.1/107686 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:24:24Z |
| publishDate | 2017 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/1076862022-10-01T15:04:08Z Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd Szeto, Gregory 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 Szeto, Gregory 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. 2017-03-24T14:11:49Z 2017-03-24T14:11:49Z 2016-09 2015-12 Article http://purl.org/eprint/type/JournalArticle 2041-1723 http://hdl.handle.net/1721.1/107686 Wang, Zichen et al. “Extraction and Analysis of Signatures from the Gene Expression Omnibus by the Crowd.” Nature Communications 7 (2016): 12846. https://orcid.org/0000-0001-7604-1333 en_US http://dx.doi.org/10.1038/ncomms12846 Nature Communications Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/ application/pdf Nature Publishing Group Nature |
| spellingShingle | Szeto, Gregory Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd |
| title | Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd |
| title_full | Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd |
| title_fullStr | Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd |
| title_full_unstemmed | Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd |
| title_short | Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd |
| title_sort | extraction and analysis of signatures from the gene expression omnibus by the crowd |
| url | http://hdl.handle.net/1721.1/107686 https://orcid.org/0000-0001-7604-1333 |
| work_keys_str_mv | AT szetogregory extractionandanalysisofsignaturesfromthegeneexpressionomnibusbythecrowd |