Filipe G Vieira1, Anders Albrechtsen2, Rasmus Nielsen3. 1. Centre for GeoGenetics, Natural History Museum of Denmark. 2. Department of Biology, University of Copenhagen, Copenhagen, Denmark and. 3. Department of Biology, University of Copenhagen, Copenhagen, Denmark and Department of Integrative Biology, University of California, Berkeley, USA.
Abstract
MOTIVATION: The amount of IBD in an individual depends on the relatedness of the individual's parents. However, it can also provide information regarding mating system, past history and effective size of the population from which the individual has been sampled. RESULTS: Here, we present a new method for estimating inbreeding IBD tracts from low coverage NGS data. Contrary to other methods that use genotype data, the one presented here uses genotype likelihoods to take the uncertainty of the data into account. We benchmark it under a wide range of biologically relevant conditions and show that the new method provides a marked increase in accuracy even at low coverage. AVAILABILITY AND IMPLEMENTATION: The methods presented in this work were implemented in C/C ++ and are freely available for non-commercial use from https://github.com/fgvieira/ngsF-HMM CONTACT: fgvieira@snm.ku.dk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: The amount of IBD in an individual depends on the relatedness of the individual's parents. However, it can also provide information regarding mating system, past history and effective size of the population from which the individual has been sampled. RESULTS: Here, we present a new method for estimating inbreeding IBD tracts from low coverage NGS data. Contrary to other methods that use genotype data, the one presented here uses genotype likelihoods to take the uncertainty of the data into account. We benchmark it under a wide range of biologically relevant conditions and show that the new method provides a marked increase in accuracy even at low coverage. AVAILABILITY AND IMPLEMENTATION: The methods presented in this work were implemented in C/C ++ and are freely available for non-commercial use from https://github.com/fgvieira/ngsF-HMM CONTACT: fgvieira@snm.ku.dk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Emma L Carroll; Mike W Bruford; J Andrew DeWoody; Gregoire Leroy; Alan Strand; Lisette Waits; Jinliang Wang Journal: Evol Appl Date: 2018-03-24 Impact factor: 5.183
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