ascatNgs: Identifying Somatically Acquired Copy-Number Alterations from Whole-Genome Sequencing Data.
ascatNgs: Identifying Somatically Acquired Copy-Number Alterations from Whole-Genome Sequencing Data.
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DOI：
10.1002/cpbi.17
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发表时间：
2016-12-08
影响因子：
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通讯作者：
Campbell PJ
中科院分区：
文献类型：
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作者：
Raine KM;Van Loo P;Wedge DC;Jones D;Menzies A;Butler AP;Teague JW;Tarpey P;Nik-Zainal S;Campbell PJ
我们开发了ascatNgs来帮助研究人员进行肿瘤的等位基因特异性拷贝数分析（ASCAT）。当与匹配的正常样本进行比较时，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的量，称为异常细胞分数（ACF）。ASCAT本身是一个R包，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。我们的代码可以在我们的GitHub网站（https：//github.com/cancerit）上找到。本单元描述了“一次性”执行和更适合大规模计算场的方法。
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.