ascatNgs: Identifying Somatically Acquired Copy-Number Alterations from Whole-Genome Sequencing Data

Q1 Biochemistry, Genetics and Molecular Biology

Current protocols in bioinformatics Pub Date : 2016-12-08 DOI:10.1002/cpbi.17

Keiran M. Raine, Peter Van Loo, David C. Wedge, David Jones, Andrew Menzies, Adam P. Butler, Jon W. Teague, Patrick Tarpey, Serena Nik-Zainal, Peter J. Campbell

引用次数: 108

Abstract

We have developed ascatNgs to aid researchers in carrying out Allele-Specific Copy number Analysis of Tumours (ASCAT). ASCAT is capable of detecting DNA copy number changes affecting a tumor genome when comparing to a matched normal sample. Additionally, the algorithm estimates the amount of tumor DNA in the sample, known as Aberrant Cell Fraction (ACF). ASCAT itself is an R-package which requires the generation of many file types. Here, we present a suite of tools to help handle this for the user. Our code is available on our GitHub site (https://github.com/cancerit). This unit describes both ‘one-shot’ execution and approaches more suitable for large-scale compute farms. © 2016 by John Wiley & Sons, Inc.

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ascatNgs:从全基因组测序数据中识别体细胞获得的拷贝数改变

我们开发了ascatgs，以帮助研究人员进行肿瘤等位基因特异性拷贝数分析(ASCAT)。与匹配的正常样本相比，ASCAT能够检测影响肿瘤基因组的DNA拷贝数变化。此外，该算法估计样本中肿瘤DNA的数量，称为异常细胞分数(ACF)。ASCAT本身是一个r包，它需要生成许多文件类型。在这里，我们提供了一套工具来帮助用户处理这个问题。我们的代码可在我们的GitHub网站(https://github.com/cancerit)。本单元描述了“一次性”执行和更适合大规模计算场的方法。©2016 by John Wiley &儿子,Inc。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Current protocols in bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry

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