New Results

hmmIBD: software to infer pairwise identity by descent between haploid genotypes

Stephen F.Schaffner,Aimee R.Taylor,WesleyWong,Dyann F.Wirth,Daniel E.Neafsey

doi: https://doi.org/10.1101/188078

Stephen F. Schaffner

1Infectious Disease and Microbiome Program, Broad Institute, Cambridge, MA, 02142USA

3Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115.

Aimee R. Taylor

1Infectious Disease and Microbiome Program, Broad Institute, Cambridge, MA, 02142USA

2Department of Epidemiology and Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, Boston, MA 02115,USA

Wesley Wong

3Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115.

Dyann F. Wirth

1Infectious Disease and Microbiome Program, Broad Institute, Cambridge, MA, 02142USA

3Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115.

Daniel E. Neafsey

1Infectious Disease and Microbiome Program, Broad Institute, Cambridge, MA, 02142USA

3Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115.

Abstract

Summary We introduce hmmIBD, software to estimate pairwise identity by decent between haploid genomes, such as those of the malaria parasite, sampled from one or more populations. We verified hmmIBD using simulated data, benchmarked it against a previously published method for detecting IBD within populations, and demonstrated its utility usingPlasmodium falciparum data from Cambodia and Ghana.

Supplementary information Supplementary data include Appendices S1, S2 and S3, and are available online.

Availability and Implemetation Source code written in C99/C11-compliant C and requiring no external libraries, is freely available for download athttps://github.com/glipsnort/hmmIBD/releases, alongside test datasets.

Contactsfs{at}broadinstitute.org

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