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GARLIC: Genomic Autozygosity Regions Likelihood-based Inference and Classification.
Szpiech, Zachary A; Blant, Alexandra; Pemberton, Trevor J.
Afiliação
  • Szpiech ZA; Department of Bioengineering and Therapeutic Sciences, University of California - San Francisco, San Francisco, CA 94158, USA.
  • Blant A; Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB R3E 0J9, Canada.
  • Pemberton TJ; Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB R3E 0J9, Canada.
Bioinformatics ; 33(13): 2059-2062, 2017 Jul 01.
Article em En | MEDLINE | ID: mdl-28205676
SUMMARY: 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. CONTACT: zachary.szpiech@ucsf.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article