Department of Computer Science, Aalto University School of Science, FI-00076 Aalto, Finland.
Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland.
Bioinformatics. 2018 Dec 1;34(23):4112-4114. doi: 10.1093/bioinformatics/bty460.
Co-localization of trait associated SNPs for specific transcription-factor binding sites or regulatory regions in the genome can yield profound insight into underlying causal mechanisms. Analysis is complicated because the truly causal SNPs are generally unknown and can be either SNPs reported in GWAS studies or other proxy SNPs in their linkage disequilibrium. Hence, a comprehensive pipeline for SNP co-localization analysis that utilizes all relevant information about both the genotyped SNPs and their proxies is needed.
We developed an R package snpEnrichR for SNP co-localization analysis. The software integrates different tools for random SNP generation and genome co-localization analysis to automatize and help users to create custom SNP co-localization analysis. We show via an example that including proxy SNPs in SNP co-localization analysis enhances the sensitivity of co-localization detection.
The software is available at https://github.com/kartiek/snpEnrichR.
在基因组中特定转录因子结合位点或调控区域的相关 SNP 的共定位，可以深入了解潜在的因果机制。分析比较复杂，因为真正的因果 SNP 通常是未知的，它们可以是 GWAS 研究中报道的 SNP，也可以是其连锁不平衡中的其他替代 SNP。因此，需要一个综合的 SNP 共定位分析管道，该管道利用了关于已分型 SNP 及其替代物的所有相关信息。
我们开发了一个用于 SNP 共定位分析的 R 包 snpEnrichR。该软件集成了不同的随机 SNP 生成工具和基因组共定位分析工具，以实现自动化并帮助用户创建自定义 SNP 共定位分析。我们通过一个例子表明，在 SNP 共定位分析中包含替代 SNP 可以提高共定位检测的灵敏度。
该软件可在 https://github.com/kartiek/snpEnrichR 上获得。
