{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T18:36:48Z","timestamp":1777315008923,"version":"3.51.4"},"reference-count":30,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2016,12,20]],"date-time":"2016-12-20T00:00:00Z","timestamp":1482192000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000060","name":"National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["f1000research.com"],"crossmark-restriction":false},"short-container-title":["F1000Res"],"abstract":"<ns4:p>\n                    <ns4:bold>Background<\/ns4:bold>\n                    : 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.\n                  <\/ns4:p>\n                  <ns4:p\/>\n                  <ns4:p>\n                    <ns4:bold>Methods:<\/ns4:bold>\n                    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 corresponding mouse models. Meta-analyses were performed in OMiCC using comparisons constructed by the participants to identify 1) gene expression signatures for each disease (disease versus healthy controls at the gene expression and biological pathway levels), 2) conserved signatures across all diseases within each species (pan-disease signatures), and 3) conserved signatures between species for each disease and across all diseases (cross-species signatures).\n                  <\/ns4:p>\n                  <ns4:p\/>\n                  <ns4:p>\n                    <ns4:bold>Results:<\/ns4:bold>\n                    A large number of differentially expressed genes were identified for each disease based on meta-analysis, with observed overlap among diseases both within and across species. Gene set\/pathway enrichment of upregulated genes suggested conserved signatures (e.g., interferon) across all human and mouse conditions.\n                  <\/ns4:p>\n                  <ns4:p\/>\n                  <ns4:p>\n                    <ns4:bold>Conclusions:<\/ns4:bold>\n                    Our Jamboree exercise provides evidence that when enabled by appropriate tools, a \"crowd\" of biologists can work together to accelerate the pace by which the increasingly large amounts of public data can be reused and meta-analyzed for generating and testing hypotheses. Our encouraging experience suggests that a similar crowdsourcing approach can be used to explore other biological questions.\n                  <\/ns4:p>","DOI":"10.12688\/f1000research.10465.1","type":"journal-article","created":{"date-parts":[[2016,12,20]],"date-time":"2016-12-20T09:30:02Z","timestamp":1482226202000},"page":"2884","update-policy":"https:\/\/doi.org\/10.12688\/f1000research.crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Meta-analysis of crowdsourced data compendia suggests pan-disease transcriptional signatures of autoimmunity"],"prefix":"10.12688","volume":"5","author":[{"given":"William W.","family":"Lau","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rachel","family":"Sparks","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"OMiCC Jamboree Working Group","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3186-3047","authenticated-orcid":false,"given":"John S.","family":"Tsang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2560","published-online":{"date-parts":[[2016,12,20]]},"reference":[{"key":"ref-1","doi-asserted-by":"publisher","first-page":"89-99","DOI":"10.1038\/nrg3394","article-title":"Reuse of public genome-wide gene expression data.","volume":"14","author":"J Rung","year":"2013","journal-title":"Nat Rev Genet."},{"key":"ref-2","doi-asserted-by":"publisher","first-page":"470-86","DOI":"10.1038\/nrg.2016.69","article-title":"Crowdsourcing biomedical research: leveraging communities as innovation engines.","volume":"17","author":"J Saez-Rodriguez","year":"2016","journal-title":"Nat Rev Genet."},{"key":"ref-3","doi-asserted-by":"publisher","first-page":"e230","DOI":"10.2196\/jmir.6365","article-title":"Datathons and Software to Promote Reproducible Research.","volume":"18","author":"L Celi","year":"2016","journal-title":"J Med Internet Res."},{"key":"ref-4","doi-asserted-by":"publisher","first-page":"803-6","DOI":"10.1038\/nbt.3603","article-title":"A crowdsourcing approach for reusing and meta-analyzing gene expression data.","volume":"34","author":"N Shah","year":"2016","journal-title":"Nat Biotechnol."},{"key":"ref-5","doi-asserted-by":"publisher","DOI":"10.1016\/j.immuni.2016.12.008","article-title":"Expanding the immunology toolbox: embracing public-data reuse and crowdsourcing.","author":"R Sparks","year":"2016","journal-title":"Immunity."},{"key":"ref-6","doi-asserted-by":"publisher","first-page":"3507-12","DOI":"10.1073\/pnas.1222878110","article-title":"Genomic responses in mouse models poorly mimic human inflammatory diseases.","volume":"110","author":"J Seok","year":"2013","journal-title":"Proc Natl Acad Sci U S A."},{"key":"ref-7","doi-asserted-by":"publisher","first-page":"121-30","DOI":"10.1016\/j.bcp.2013.06.014","article-title":"Animal models of human disease: inflammation.","volume":"87","author":"D Webb","year":"2014","journal-title":"Biochem Pharmacol."},{"key":"ref-8","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1186\/s13075-014-0489-x","article-title":"Shared signatures between rheumatoid arthritis, systemic lupus erythematosus and Sj\u00f6gren's syndrome uncovered through gene expression meta-analysis.","volume":"16","author":"D Toro-Dom\u00ednguez","year":"2014","journal-title":"Arthritis Res Ther."},{"key":"ref-9","doi-asserted-by":"publisher","first-page":"194-206","DOI":"10.1016\/j.immuni.2015.12.006","article-title":"Compendium of Immune Signatures Identifies Conserved and Species-Specific Biology in Response to Inflammation.","volume":"44","author":"J Godec","year":"2016","journal-title":"Immunity."},{"key":"ref-10","doi-asserted-by":"publisher","first-page":"1167-72","DOI":"10.1073\/pnas.1401965111","article-title":"Genomic responses in mouse models greatly mimic human inflammatory diseases.","volume":"112","author":"K Takao","year":"2015","journal-title":"Proc Natl Acad Sci U S A."},{"key":"ref-11","doi-asserted-by":"publisher","first-page":"2825-7","DOI":"10.1093\/bioinformatics\/btl476","article-title":"RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysis.","volume":"22","author":"F Hong","year":"2006","journal-title":"Bioinformatics."},{"key":"ref-12","doi-asserted-by":"publisher","first-page":"284-7","DOI":"10.1089\/omi.2011.0118","article-title":"clusterProfiler: an R package for comparing biological themes among gene clusters.","volume":"16","author":"G Yu","year":"2012","journal-title":"OMICS."},{"key":"ref-13","doi-asserted-by":"publisher","first-page":"477-9","DOI":"10.1039\/c5mb00663e","article-title":"ReactomePA: an R\/Bioconductor package for reactome pathway analysis and visualization.","volume":"12","author":"G Yu","year":"2016","journal-title":"Mol Biosyst."},{"key":"ref-14","doi-asserted-by":"publisher","first-page":"W305-11","DOI":"10.1093\/nar\/gkp427","article-title":"ToppGene Suite for gene list enrichment analysis and candidate gene prioritization.","volume":"37","author":"J Chen","year":"2009","journal-title":"Nucleic Acids Res."},{"key":"ref-15","doi-asserted-by":"publisher","first-page":"3785-99","DOI":"10.1093\/nar\/gkr1265","article-title":"Comprehensive literature review and statistical considerations for microarray meta-analysis.","volume":"40","author":"G Tseng","year":"2012","journal-title":"Nucleic Acids Res."},{"key":"ref-16","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkw797","article-title":"Methods to increase reproducibility in differential gene expression via meta-analysis.","author":"T Sweeney","year":"2016","journal-title":"Nucleic Acids Res."},{"key":"ref-17","doi-asserted-by":"publisher","first-page":"2610-5","DOI":"10.1073\/pnas.0337679100","article-title":"Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus.","volume":"100","author":"E Baechler","year":"2003","journal-title":"Proc Natl Acad Sci U S A."},{"key":"ref-18","doi-asserted-by":"publisher","first-page":"711-23","DOI":"10.1084\/jem.20021553","article-title":"Interferon and granulopoiesis signatures in systemic lupus erythematosus blood.","volume":"197","author":"L Bennett","year":"2003","journal-title":"J Exp Med."},{"key":"ref-19","doi-asserted-by":"publisher","first-page":"2029-36","DOI":"10.1136\/ard.2011.150326","article-title":"Patients with systemic lupus erythematosus, myositis, rheumatoid arthritis and scleroderma share activation of a common type I interferon pathway.","volume":"70","author":"B Higgs","year":"2011","journal-title":"Ann Rheum Dis."},{"key":"ref-20","doi-asserted-by":"publisher","first-page":"219-29","DOI":"10.1002\/art.30087","article-title":"Interferon-\u03b1 accelerates murine systemic lupus erythematosus in a T cell-dependent manner.","volume":"63","author":"Z Liu","year":"2011","journal-title":"Arthritis Rheum."},{"key":"ref-21","doi-asserted-by":"publisher","first-page":"716-30","DOI":"10.1038\/nrrheum.2016.186","article-title":"New insights into the immunopathogenesis of systemic lupus erythematosus.","volume":"12","author":"G Tsokos","year":"2016","journal-title":"Nat Rev Rheumatol."},{"key":"ref-22","doi-asserted-by":"publisher","first-page":"531-41","DOI":"10.1038\/nrrheum.2009.182","article-title":"Treatment of rheumatoid arthritis: state of the art 2009.","volume":"5","author":"R van Vollenhoven","year":"2009","journal-title":"Nat Rev Rheumatol."},{"key":"ref-23","doi-asserted-by":"publisher","first-page":"458-9","DOI":"10.1038\/ncprheum0292","article-title":"Mode of action of hydroxychloroquine in RA-evidence of an inhibitory effect on toll-like receptor signaling.","volume":"2","author":"D Kyburz","year":"2006","journal-title":"Nat Clin Pract Rheumatol."},{"key":"ref-24","doi-asserted-by":"publisher","first-page":"746-57","DOI":"10.1111\/eci.12101","article-title":"Platelets and autoimmunity.","volume":"43","author":"K Habets","year":"2013","journal-title":"Eur J Clin Invest."},{"key":"ref-25","doi-asserted-by":"publisher","first-page":"580-3","DOI":"10.1126\/science.1181928","article-title":"Platelets amplify inflammation in arthritis via collagen-dependent microparticle production.","volume":"327","author":"E Boilard","year":"2010","journal-title":"Science."},{"key":"ref-26","doi-asserted-by":"publisher","first-page":"534-42","DOI":"10.1038\/nrrheum.2012.118","article-title":"Platelets: active players in the pathogenesis of arthritis and SLE.","volume":"8","author":"E Boilard","year":"2012","journal-title":"Nat Rev Rheumatol."},{"key":"ref-27","doi-asserted-by":"publisher","DOI":"10.5256\/f1000research.10465.d146994","article-title":"Dataset 1 in: Meta-analysis of crowdsourced data compendia suggests pan-disease transcriptional signatures of autoimmunity.","author":"W Lau","year":"2016","journal-title":"F1000Research."},{"key":"ref-28","doi-asserted-by":"publisher","DOI":"10.5256\/f1000research.10465.d146995","article-title":"Dataset 2 in: Meta-analysis of crowdsourced data compendia suggests pan-disease transcriptional signatures of autoimmunity.","author":"W Lau","year":"2016","journal-title":"F1000Research."},{"key":"ref-29","doi-asserted-by":"publisher","DOI":"10.5256\/f1000research.10465.d146996","article-title":"Dataset 3 in: Meta-analysis of crowdsourced data compendia suggests pan-disease transcriptional signatures of autoimmunity.","author":"W Lau","year":"2016","journal-title":"F1000Research."},{"key":"ref-30","doi-asserted-by":"publisher","DOI":"10.5256\/f1000research.10465.d146997","article-title":"Dataset 4 in: Meta-analysis of crowdsourced data compendia suggests pan-disease transcriptional signatures of autoimmunity.","author":"W 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status","group":{"name":"current-referee-status","label":"Current Referee Status"}},{"value":"10.5256\/f1000research.11275.r19356, Hans Lehrach, Hans-J\u00f6rg Warnatz, Thomas Risch, Department Vertebrate Genomics, Max Planck Institute for Molecular Genetics (MPIMG), Berlin, Germany, 16 Jan 2017, version 1, indexed","URL":"https:\/\/f1000research.com\/articles\/5-2884\/v1#referee-response-19356","order":0,"name":"referee-response-19356","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.11275.r21277, Markus Riester, Novartis Institutes for BioMedical Research, Cambridge, MA, USA, 18 Apr 2017, version 1, indexed","URL":"https:\/\/f1000research.com\/articles\/5-2884\/v1#referee-response-21277","order":1,"name":"referee-response-21277","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"This research was funded by the Intramural Programs of the National Institute of Allergy and Infectious Diseases (NIAID) and the Center for Information Technology (CIT) at the National Institutes of Health.","order":2,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Data associated with the article are available under the terms of the Creative Commons Zero \"No rights reserved\" data waiver (CC0 1.0 Public domain dedication).","order":0,"name":"copyright-info","label":"Copyright"}]}}