MSignatureDB: a database for deciphering mutational signatures in human cancers. Issue Volume 46:Issue D1(2018) (14th November 2017)

• Record Type: Journal Article
• Authors: Huang, Po-Jung; Chiu, Ling-Ya; Lee, Chi-Ching; Yeh, Yuan-Ming; Huang, Kuo-Yang; Chiu, Cheng-Hsun; Tang, Petrus
• Is Part Of: Nucleic acids research. Volume 46:Issue D1(2018)
• Page Start: D964
• Page End: D970
• Publication Date: 2017-11-14
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkx1133
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: 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.