{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:28:09Z","timestamp":1776086889026,"version":"3.50.1"},"reference-count":13,"publisher":"Oxford University Press (OUP)","issue":"W1","license":[{"start":{"date-parts":[[2021,5,29]],"date-time":"2021-05-29T00:00:00Z","timestamp":1622246400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"National Teaching Center for Experimental Biology, Peking University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>In 2017, we released GEPIA (Gene Expression Profiling Interactive Analysis) webserver to facilitate the widely used analyses based on the bulk gene expression datasets in the TCGA and the GTEx projects, providing the biologists and clinicians with a handy tool to perform comprehensive and complex data mining tasks. Recently, the deconvolution tools have led to revolutionary trends to resolve bulk RNA datasets at cell type-level resolution, interrogating the characteristics of different cell types in cancer and controlled cohorts became an important strategy to investigate the biological questions. Thus, we present GEPIA2021, a standalone extension of GEPIA, allowing users to perform multiple interactive analysis based on the deconvolution results, including cell type-level proportion comparison, correlation analysis, differential expression, and survival analysis. With GEPIA2021, experimental biologists could easily explore the large TCGA and GTEx datasets and validate their hypotheses in an enhanced resolution. GEPIA2021 is publicly accessible at http:\/\/gepia2021.cancer-pku.cn\/.<\/jats:p>","DOI":"10.1093\/nar\/gkab418","type":"journal-article","created":{"date-parts":[[2021,5,3]],"date-time":"2021-05-03T11:07:51Z","timestamp":1620040071000},"page":"W242-W246","source":"Crossref","is-referenced-by-count":421,"title":["GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA"],"prefix":"10.1093","volume":"49","author":[{"given":"Chenwei","family":"Li","sequence":"first","affiliation":[{"name":"School of Life Sciences, BIOPIC and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China"},{"name":"Analytical Biosciences Limited, Beijing, China"}]},{"given":"Zefang","family":"Tang","sequence":"additional","affiliation":[{"name":"IBM China Research Lab, Beijing, China"}]},{"given":"Wenjie","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Peking University, Beijing, China"}]},{"given":"Zhaochen","family":"Ye","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2049-9975","authenticated-orcid":false,"given":"Fenglin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Peking University, Beijing, China"}]}],"member":"286","published-online":{"date-parts":[[2021,5,29]]},"reference":[{"key":"2021070812114348100_B1","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1038\/ng.2764","article-title":"The Cancer Genome Atlas Pan-Cancer analysis project","volume":"45","author":"Cancer Genome Atlas Research Network","year":"2013","journal-title":"Nat. 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