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DysRegSig: an R package for identifying gene dysregulations and building mechanistic signatures in cancer
SUMMARY: Dysfunctional regulations of gene expression programs relevant to fundamental cell processes can drive carcinogenesis. Therefore, systematically identifying dysregulation events is an effective path for understanding carcinogenesis and provides insightful clues to build predictive signature...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058765/ https://www.ncbi.nlm.nih.gov/pubmed/32717036 http://dx.doi.org/10.1093/bioinformatics/btaa688 |
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author | Li, Quanxue Dai, Wentao Liu, Jixiang Sang, Qingqing Li, Yi-Xue Li, Yuan-Yuan |
author_facet | Li, Quanxue Dai, Wentao Liu, Jixiang Sang, Qingqing Li, Yi-Xue Li, Yuan-Yuan |
author_sort | Li, Quanxue |
collection | PubMed |
description | SUMMARY: Dysfunctional regulations of gene expression programs relevant to fundamental cell processes can drive carcinogenesis. Therefore, systematically identifying dysregulation events is an effective path for understanding carcinogenesis and provides insightful clues to build predictive signatures with mechanistic interpretability for cancer precision medicine. Here, we implemented a machine learning-based gene dysregulation analysis framework in an R package, DysRegSig, which is capable of exploring gene dysregulations from high-dimensional data and building mechanistic signature based on gene dysregulations. DysRegSig can serve as an easy-to-use tool to facilitate gene dysregulation analysis and follow-up analysis. AVAILABILITY AND IMPLEMENTATION: The source code and user’s guide of DysRegSig are freely available at Github: https://github.com/SCBIT-YYLab/DysRegSig. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8058765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-80587652021-04-28 DysRegSig: an R package for identifying gene dysregulations and building mechanistic signatures in cancer Li, Quanxue Dai, Wentao Liu, Jixiang Sang, Qingqing Li, Yi-Xue Li, Yuan-Yuan Bioinformatics Applications Notes SUMMARY: Dysfunctional regulations of gene expression programs relevant to fundamental cell processes can drive carcinogenesis. Therefore, systematically identifying dysregulation events is an effective path for understanding carcinogenesis and provides insightful clues to build predictive signatures with mechanistic interpretability for cancer precision medicine. Here, we implemented a machine learning-based gene dysregulation analysis framework in an R package, DysRegSig, which is capable of exploring gene dysregulations from high-dimensional data and building mechanistic signature based on gene dysregulations. DysRegSig can serve as an easy-to-use tool to facilitate gene dysregulation analysis and follow-up analysis. AVAILABILITY AND IMPLEMENTATION: The source code and user’s guide of DysRegSig are freely available at Github: https://github.com/SCBIT-YYLab/DysRegSig. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-07-27 /pmc/articles/PMC8058765/ /pubmed/32717036 http://dx.doi.org/10.1093/bioinformatics/btaa688 Text en © The Author(s) 2020. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Li, Quanxue Dai, Wentao Liu, Jixiang Sang, Qingqing Li, Yi-Xue Li, Yuan-Yuan DysRegSig: an R package for identifying gene dysregulations and building mechanistic signatures in cancer |
title | DysRegSig: an R package for identifying gene dysregulations and building mechanistic signatures in cancer |
title_full | DysRegSig: an R package for identifying gene dysregulations and building mechanistic signatures in cancer |
title_fullStr | DysRegSig: an R package for identifying gene dysregulations and building mechanistic signatures in cancer |
title_full_unstemmed | DysRegSig: an R package for identifying gene dysregulations and building mechanistic signatures in cancer |
title_short | DysRegSig: an R package for identifying gene dysregulations and building mechanistic signatures in cancer |
title_sort | dysregsig: an r package for identifying gene dysregulations and building mechanistic signatures in cancer |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058765/ https://www.ncbi.nlm.nih.gov/pubmed/32717036 http://dx.doi.org/10.1093/bioinformatics/btaa688 |
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