变色
索引
计算生物学
癌症基因组测序
基因组
生物
DNA测序
工作流程
拷贝数变化
基因组学
计算机科学
人类基因组
单细胞测序
遗传学
外显子组测序
表型
基因
单核苷酸多态性
DNA
基因组不稳定性
DNA损伤
基因型
数据库
作者
Sebastian Lange,Thomas Engleitner,Sebastian Mueller,Roman Maresch,Maximilian Zwiebel,Laura González-Silva,Günter Schneider,Ruby Banerjee,Fengtang Yang,George S. Vassiliou,Mathias Friedrich,Dieter Saur,Ignacio Varela,Roland Rad
出处
期刊:Nature Protocols
[Springer Nature]
日期:2020-01-06
卷期号:15 (2): 266-315
被引量:31
标识
DOI:10.1038/s41596-019-0234-7
摘要
Mouse models of human cancer have transformed our ability to link genetics, molecular mechanisms and phenotypes. Both reverse and forward genetics in mice are currently gaining momentum through advances in next-generation sequencing (NGS). Methodologies to analyze sequencing data were, however, developed for humans and hence do not account for species-specific differences in genome structures and experimental setups. Here, we describe standardized computational pipelines specifically tailored to the analysis of mouse genomic data. We present novel tools and workflows for the detection of different alteration types, including single-nucleotide variants (SNVs), small insertions and deletions (indels), copy-number variations (CNVs), loss of heterozygosity (LOH) and complex rearrangements, such as in chromothripsis. Workflows have been extensively validated and cross-compared using multiple methodologies. We also give step-by-step guidance on the execution of individual analysis types, provide advice on data interpretation and make the complete code available online. The protocol takes 2–7 d, depending on the desired analyses. Here, the authors present standardized computational pipelines tailored specifically to the analysis of cancer genome sequencing data from mice. The protocol enables detection of single-nucleotide variants, indels, copy-number variations, loss of heterozygosity and complex rearrangements such as those of chromothripsis.
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