Department of Bioengineering and Therapeutic Sciences, University of California - San Francisco, San Francisco, CA 94158, USA.
Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB R3E 0J9, Canada.
Bioinformatics. 2017 Jul 1;33(13):2059-2062. doi: 10.1093/bioinformatics/btx102.
Runs of homozygosity (ROH) are important genomic features that manifest when identical-by-descent haplotypes are inherited from parents. Their length distributions and genomic locations are informative about population history and they are useful for mapping recessive loci contributing to both Mendelian and complex disease risk. Here, we present software implementing a model-based method ( Pemberton et al., 2012 ) for inferring ROH in genome-wide SNP datasets that incorporates population-specific parameters and a genotyping error rate as well as provides a length-based classification module to identify biologically interesting classes of ROH. Using simulations, we evaluate the performance of this method.
GARLIC is written in C ++. Source code and pre-compiled binaries (Windows, OSX and Linux) are hosted on GitHub ( https://github.com/szpiech/garlic ) under the GNU General Public License version 3.
Supplementary data are available at Bioinformatics online.
纯合片段（ROH）是重要的基因组特征，当来自父母的同一位点基因型（identical-by-descent haplotypes）被遗传时就会表现出来。它们的长度分布和基因组位置提供了有关群体历史的信息，并且对于定位隐性遗传的基因座（这些基因座可能导致孟德尔疾病和复杂疾病的风险）非常有用。在这里，我们提出了一个基于模型的软件，该软件实现了一种推断全基因组 SNP 数据中 ROH 的方法（Pemberton 等人，2012 年），该方法整合了特定于群体的参数和基因分型错误率，同时提供了一个基于长度的分类模块，用于识别具有生物学意义的 ROH 类别。我们通过模拟来评估该方法的性能。
GARLIC 是用 C++编写的。源代码和预编译的二进制文件（Windows、OSX 和 Linux）在 GitHub（https://github.com/szpiech/garlic）上以 GNU 通用公共许可证第 3 版的形式托管。
补充数据可在 Bioinformatics 在线获取。
