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mSignatureDB: a database for deciphering mutational signatures in human cancers
Cancer is a genetic disease caused by somatic mutations; however, the understanding of the causative biological processes generating these mutations is limited. A cancer genome bears the cumulative effects of mutational processes during tumor development. Deciphering mutational signatures in cancer...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753213/ https://www.ncbi.nlm.nih.gov/pubmed/29145625 http://dx.doi.org/10.1093/nar/gkx1133 |
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author | Huang, Po-Jung Chiu, Ling-Ya Lee, Chi-Ching Yeh, Yuan-Ming Huang, Kuo-Yang Chiu, Cheng-Hsun Tang, Petrus |
author_facet | Huang, Po-Jung Chiu, Ling-Ya Lee, Chi-Ching Yeh, Yuan-Ming Huang, Kuo-Yang Chiu, Cheng-Hsun Tang, Petrus |
author_sort | Huang, Po-Jung |
collection | PubMed |
description | Cancer is a genetic disease caused by somatic mutations; however, the understanding of the causative biological processes generating these mutations is limited. A cancer genome bears the cumulative effects of mutational processes during tumor development. Deciphering mutational signatures in cancer is a new topic in cancer research. The Wellcome Trust Sanger Institute (WTSI) has categorized 30 reference signatures in the COSMIC database based on the analyses of ∼10 000 sequencing datasets from TCGA and ICGC. Large cohorts and bioinformatics skills are required to perform the same analysis as WTSI. The quantification of known signatures in custom cohorts is not possible under the current framework of the COSMIC database, which motivates us to construct a database for mutational signatures in cancers and make such analyses more accessible to general researchers. mSignatureDB (http://tardis.cgu.edu.tw/msignaturedb) integrates R packages and in-house scripts to determine the contributions of the published signatures in 15 780 individual tumors from 73 TCGA/ICGC cancer projects, making comparison of signature patterns within and between projects become possible. mSignatureDB also allows users to perform signature analysis on their own datasets, quantifying contributions of signatures at sample resolution, which is a unique feature of mSignatureDB not available in other related databases. |
format | Online Article Text |
id | pubmed-5753213 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-57532132018-01-05 mSignatureDB: a database for deciphering mutational signatures in human cancers Huang, Po-Jung Chiu, Ling-Ya Lee, Chi-Ching Yeh, Yuan-Ming Huang, Kuo-Yang Chiu, Cheng-Hsun Tang, Petrus Nucleic Acids Res Database Issue Cancer is a genetic disease caused by somatic mutations; however, the understanding of the causative biological processes generating these mutations is limited. A cancer genome bears the cumulative effects of mutational processes during tumor development. Deciphering mutational signatures in cancer is a new topic in cancer research. The Wellcome Trust Sanger Institute (WTSI) has categorized 30 reference signatures in the COSMIC database based on the analyses of ∼10 000 sequencing datasets from TCGA and ICGC. Large cohorts and bioinformatics skills are required to perform the same analysis as WTSI. The quantification of known signatures in custom cohorts is not possible under the current framework of the COSMIC database, which motivates us to construct a database for mutational signatures in cancers and make such analyses more accessible to general researchers. mSignatureDB (http://tardis.cgu.edu.tw/msignaturedb) integrates R packages and in-house scripts to determine the contributions of the published signatures in 15 780 individual tumors from 73 TCGA/ICGC cancer projects, making comparison of signature patterns within and between projects become possible. mSignatureDB also allows users to perform signature analysis on their own datasets, quantifying contributions of signatures at sample resolution, which is a unique feature of mSignatureDB not available in other related databases. Oxford University Press 2018-01-04 2017-11-14 /pmc/articles/PMC5753213/ /pubmed/29145625 http://dx.doi.org/10.1093/nar/gkx1133 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://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 | Database Issue Huang, Po-Jung Chiu, Ling-Ya Lee, Chi-Ching Yeh, Yuan-Ming Huang, Kuo-Yang Chiu, Cheng-Hsun Tang, Petrus mSignatureDB: a database for deciphering mutational signatures in human cancers |
title | mSignatureDB: a database for deciphering mutational signatures in human cancers |
title_full | mSignatureDB: a database for deciphering mutational signatures in human cancers |
title_fullStr | mSignatureDB: a database for deciphering mutational signatures in human cancers |
title_full_unstemmed | mSignatureDB: a database for deciphering mutational signatures in human cancers |
title_short | mSignatureDB: a database for deciphering mutational signatures in human cancers |
title_sort | msignaturedb: a database for deciphering mutational signatures in human cancers |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753213/ https://www.ncbi.nlm.nih.gov/pubmed/29145625 http://dx.doi.org/10.1093/nar/gkx1133 |
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