1 Department of Computer Science, Science and Technology, Aarhus University2 Bioinformatics Research Centre (BiRC), Science and Technology, Aarhus University3 Biophysics Graduate Group, University of California, Berkeley, CA, 947094 Computer Science Division, University of California, Berkeley, CA, 947095 Bioinformatics Research Centre (BiRC), Science and Technology, Aarhus University
Summary: We present a tool, diCal-IBD, for detecting identity-bydescent (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 SNP-based IBD detection methods, while retaining reasonable accuracy for IBD tracts as small as 0.1 cM. Availability: http://sourceforge.net/projects/dical-ibd Contact: firstname.lastname@example.org Supplementary Information: Available at the journal’s website.
Bioinformatics, 2014, Vol 30, Issue 23, p. 3430-3431