Python(编程语言)
计算机科学
文档
R包
源代码
遗传建筑学
开源
编码(社会科学)
数据挖掘
计算生物学
作者
Rana Aldisi,Emadeldin Hassanin,Sugirthan Sivalingam,Andreas Buness,Hannah Klinkhammer,Andreas Mayr,Holger Fröhlich,Peter Krawitz,Carlo Maj
标识
DOI:10.1093/bioinformatics/btac152
摘要
The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious variants in coding regions with larger effect sizes. However, the two kinds of genetic contributions are typically analyzed independently. Here we present GenRisk, a python package for the computation and the integration of gene scores based on the burden of rare deleterious variants and common-variants based polygenic risk scores. The derived scores can be analyzed within GenRisk to perform association tests or to derive phenotype prediction models by testing multiple classification and regression approaches. GenRisk is compatible with VCF input file formats.GenRisk is an open source publicly available python package that can be downloaded or installed from Github (https://github.com/AldisiRana/GenRisk).GenRisk documentation is available online at https://genrisk.readthedocs.io/en/latest/.
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