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Bioinformatics. 2014 Dec 1;30(23):3430-1. doi: 10.1093/bioinformatics/btu563. Epub 2014 Aug 21.

diCal-IBD: demography-aware inference of identity-by-descent tracts in unrelated individuals.

Author information

1
Bioinformatics Research Centre, Department of Computer Science, Aarhus University, 8000 Aarhus C, Denmark, Biophysics Graduate Group, Computer Science Division, Department of Statistics and Department of Integrative Biology, University of California, Berkeley, CA 94720, USA.
2
Bioinformatics Research Centre, Department of Computer Science, Aarhus University, 8000 Aarhus C, Denmark, Biophysics Graduate Group, Computer Science Division, Department of Statistics and Department of Integrative Biology, University of California, Berkeley, CA 94720, USA Bioinformatics Research Centre, Department of Computer Science, Aarhus University, 8000 Aarhus C, Denmark, Biophysics Graduate Group, Computer Science Division, Department of Statistics and Department of Integrative Biology, University of California, Berkeley, CA 94720, USA Bioinformatics Research Centre, Department of Computer Science, Aarhus University, 8000 Aarhus C, Denmark, Biophysics Graduate Group, Computer Science Division, Department of Statistics and Department of Integrative Biology, University of California, Berkeley, CA 94720, USA.

Abstract

We present a tool, diCal-IBD, for detecting identity-by-descent (IBD) tracts between pairs of genomic sequences. Our method builds on a recent demographic inference method based on the coalescent with recombination, and is able to incorporate demographic information as a prior. Simulation study shows that diCal-IBD has significantly higher recall and precision than that of existing single-nucleotide polymorphism-based IBD detection methods, while retaining reasonable accuracy for IBD tracts as small as 0.1 cM.

AVAILABILITY:

http://sourceforge.net/projects/dical-ibd.

PMID:
25147361
PMCID:
PMC4296155
DOI:
10.1093/bioinformatics/btu563
[Indexed for MEDLINE]
Free PMC Article

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