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MutSignatures:一个用于提取和分析癌症突变特征的 R 包。

MutSignatures: an R package for extraction and analysis of cancer mutational signatures.

机构信息

Department of Urology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.

Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, USA.

出版信息

Sci Rep. 2020 Oct 26;10(1):18217. doi: 10.1038/s41598-020-75062-0.

Abstract

Cancer cells accumulate somatic mutations as result of DNA damage, inaccurate repair and other mechanisms. Different genetic instability processes result in characteristic non-random patterns of DNA mutations, also known as mutational signatures. We developed mutSignatures, an integrated R-based computational framework aimed at deciphering DNA mutational signatures. Our software provides advanced functions for importing DNA variants, computing mutation types, and extracting mutational signatures via non-negative matrix factorization. Specifically, mutSignatures accepts multiple types of input data, is compatible with non-human genomes, and supports the analysis of non-standard mutation types, such as tetra-nucleotide mutation types. We applied mutSignatures to analyze somatic mutations found in smoking-related cancer datasets. We characterized mutational signatures that were consistent with those reported before in independent investigations. Our work demonstrates that selected mutational signatures correlated with specific clinical and molecular features across different cancer types, and revealed complementarity of specific mutational patterns that has not previously been identified. In conclusion, we propose mutSignatures as a powerful open-source tool for detecting the molecular determinants of cancer and gathering insights into cancer biology and treatment.

摘要

癌细胞会因 DNA 损伤、修复不准确和其他机制而积累体细胞突变。不同的遗传不稳定性过程导致特征性的非随机 DNA 突变模式,也称为突变特征。我们开发了 mutSignatures,这是一个基于 R 的集成计算框架,旨在破译 DNA 突变特征。我们的软件提供了先进的功能,用于导入 DNA 变体、计算突变类型,并通过非负矩阵分解提取突变特征。具体来说,mutSignatures 接受多种类型的输入数据,与非人类基因组兼容,并支持非标准突变类型(如四核苷酸突变类型)的分析。我们应用 mutSignatures 来分析与吸烟相关的癌症数据集。我们确定了与以前独立研究中报道的一致的突变特征。我们的工作表明,选定的突变特征与不同癌症类型中特定的临床和分子特征相关,并且揭示了以前未发现的特定突变模式的互补性。总之,我们提出 mutSignatures 是一种强大的开源工具,用于检测癌症的分子决定因素,并深入了解癌症生物学和治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dd7/7589488/68dc6b141222/41598_2020_75062_Fig1_HTML.jpg

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