Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research
Novel scripts for improved annotation and selection of variants from whole exome sequencing in cancer research
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DOI：
10.1016/j.mex.2015.03.003
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发表时间：
2015-01-01
期刊：
影响因子：
1.9
通讯作者：
Hokland, Peter
中科院分区：
文献类型：
--
作者：
Hansen, Marcus Celik;Nederby, Line;Hokland, Peter
外显子组测序正迅速成为发现致病突变的首选方法。虽然获取数据集是一个简单的过程，但后续对数据的分析和解读对于临床应用来说是一个限制步骤。因此，虽然最初的突变和变异识别可以由生物信息学家或受过训练的研究人员来进行，但像MuTect和GATK这样强大的软件包的输出对于普通生命科学家来说并不是直接有用的信息。为了消除这个问题，我们创建了互补的Wolfram脚本，这些脚本能够轻松进行下游注释和选择，这里是从血液学相关性的角度呈现的。它还为研究人员提供了通过手头完整的Mathematica编程和分析环境来扩展分析的机会。简而言之，后处理通过以下方式进行：将生殖系和体细胞变异映射到编码区域，并在Mathematica中定义变异集。在变异效应预测器中处理变异。通过提供的函数进行扩展注释、相关性评分和定义关注区域。（C）2015作者。由爱思唯尔出版集团出版。
Sequencing the exome is quickly becoming the preferred method for discovering disease-inducing mutations. While obtaining data sets is a straightforward procedure, the subsequent analysis and interpretation of the data is a limiting step for clinical applications. Thus, while the initial mutation and variant calling can be performed by a bioinformatician or trained researcher, the output from robust packages such as MuTect and GATK is not directly informative for the general life scientists. In attempt to obviate this problem we have created complementary Wolfram scripts, which enable easy downstream annotation and selection, presented here in the perspective of hematological relevance. It also provides the researcher with the opportunity to extend the analysis by having a full-fledged programming and analysis environment of Mathematica at hand. In brief, post-processing is performed by:Mapping of germ line and somatic variants to coding regions, and defining variant sets within Mathematica.Processing of variants in variant effect predictor.Extended annotation, relevance scoring and defining focus areas through the provided functions. (C) 2015 The Authors. Published by Elsevier B.V.