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Custom workflows to improve joint variant calling from multiple related tumour samples: FreeBayesSomatic and Strelka2Pass
Bioinformatics ( IF 4.4 ) Pub Date : 2021-09-01 , DOI: 10.1093/bioinformatics/btab606
S Hollizeck 1, 2 , S Q Wong 1, 2 , B Solomon 1, 2 , D Chandrananda 1, 2 , S-J Dawson 1, 2, 3
Affiliation  

Summary This work describes two novel workflows for variant calling that extend the widely used algorithms of Strelka2 and FreeBayes to call somatic mutations from multiple related tumour samples and one matched normal sample. We show that these workflows offer higher precision and recall than their single tumour-normal pair equivalents in both simulated and clinical sequencing data. Availability and implementation Source code freely available at the following link: https://atlassian.petermac.org.au/bitbucket/projects/DAW/repos/multisamplevariantcalling and executable through Janis (https://github.com/PMCC-BioinformaticsCore/janis) under the GPLv3 licence. Supplementary information Supplementary data are available at Bioinformatics online.

中文翻译:

自定义工作流程以改进来自多个相关肿瘤样本的联合变体调用:FreeBayesSomatic 和 Strelka2Pass

总结 这项工作描述了两种用于变异识别的新工作流程,它们扩展了广泛使用的 Strelka2 和 FreeBayes 算法,以从多个相关肿瘤样本和一个匹配的正常样本中识别体细胞突变。我们表明,这些工作流程在模拟和临床测序数据中提供了比它们的单个肿瘤-正常对等价物更高的精确度和召回率。可用性和实施​​源代码可在以下链接免费获得:https://atlassian.petermac.org.au/bitbucket/projects/DAW/repos/multisamplevariantcalling 并可通过 Janis (https://github.com/PMCC-BioinformaticsCore/ janis) 在 GPLv3 许可证下。补充信息 补充数据可在 Bioinformatics 在线获取。
更新日期:2021-09-01
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