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GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA
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 da...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262695/ https://www.ncbi.nlm.nih.gov/pubmed/34050758 http://dx.doi.org/10.1093/nar/gkab418 |
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author | Li, Chenwei Tang, Zefang Zhang, Wenjie Ye, Zhaochen Liu, Fenglin |
author_facet | Li, Chenwei Tang, Zefang Zhang, Wenjie Ye, Zhaochen Liu, Fenglin |
author_sort | Li, Chenwei |
collection | PubMed |
description | 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/. |
format | Online Article Text |
id | pubmed-8262695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82626952021-07-08 GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA Li, Chenwei Tang, Zefang Zhang, Wenjie Ye, Zhaochen Liu, Fenglin Nucleic Acids Res Web Server Issue 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/. Oxford University Press 2021-05-29 /pmc/articles/PMC8262695/ /pubmed/34050758 http://dx.doi.org/10.1093/nar/gkab418 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server Issue Li, Chenwei Tang, Zefang Zhang, Wenjie Ye, Zhaochen Liu, Fenglin GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA |
title | GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA |
title_full | GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA |
title_fullStr | GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA |
title_full_unstemmed | GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA |
title_short | GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA |
title_sort | gepia2021: integrating multiple deconvolution-based analysis into gepia |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262695/ https://www.ncbi.nlm.nih.gov/pubmed/34050758 http://dx.doi.org/10.1093/nar/gkab418 |
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