GARLIC: Genomic Autozygosity Regions Likelihood-based Inference and Classification

Zachary A. Szpiech, Alexandra Blant, Trevor J. Pemberton

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

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. Availability and Implementation: 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.

Original languageEnglish (US)
Pages (from-to)2059-2062
Number of pages4
JournalBioinformatics
Volume33
Issue number13
DOIs
StatePublished - Jul 1 2017

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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