Ware James S, Samocha Kaitlin E, Homsy Jason, Daly Mark J
Department of Genetics, Harvard Medical School, Boston, Massachusetts.
Broad Institute of MIT and Harvard, Cambridge, Massachusetts.
Curr Protoc Hum Genet. 2015 Oct 6;87:7.25.1-7.25.15. doi: 10.1002/0471142905.hg0725s87.
Spontaneously arising (de novo) genetic variants are important in human disease, yet every individual carries many such variants, with a median of 1 de novo variant affecting the protein-coding portion of the genome. A recently described mutational model provides a powerful framework for the robust statistical evaluation of such coding variants, enabling the interpretation of de novo variation in human disease. Here we describe a new open-source software package, denovolyzeR, that implements this model and provides tools for the analysis of de novo coding sequence variants.
自发产生(新生)的基因变异在人类疾病中很重要,然而每个人都携带许多这样的变异,其中位数为1个新生变异影响基因组的蛋白质编码部分。最近描述的一种突变模型为这类编码变异的稳健统计评估提供了一个强大的框架,能够解释人类疾病中的新生变异。在这里,我们描述了一个新的开源软件包denovolyzeR,它实现了这个模型,并提供了分析新生编码序列变异的工具。