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Am J Hum Genet. 2011 Jun 10;88(6):706-717. doi: 10.1016/j.ajhg.2011.04.023. Epub 2011 May 27.

DASH: a method for identical-by-descent haplotype mapping uncovers association with recent variation.

Author information

1
Department of Computer Science, Columbia University, New York, NY 10027, USA.
2
Department of Computer Science, Columbia University, New York, NY 10027, USA; Medical Sciences and Human Genetics, Rockefeller University, New York, NY 10065, USA.
3
Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics, The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
4
Medical Sciences and Human Genetics, Rockefeller University, New York, NY 10065, USA.
5
Program in Medical and Population Genetics, The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
6
Program in Medical and Population Genetics, The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Cardiovascular Disease Prevention Center, Cardiology Division, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
7
Program in Medical and Population Genetics, The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Center for Human Genetic Research and Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
8
Department of Computer Science, Columbia University, New York, NY 10027, USA. Electronic address: itsik@cs.columbia.edu.

Abstract

Rare variants affecting phenotype pose a unique challenge for human genetics. Although genome-wide association studies have successfully detected many common causal variants, they are underpowered in identifying disease variants that are too rare or population-specific to be imputed from a general reference panel and thus are poorly represented on commercial SNP arrays. We set out to overcome these challenges and detect association between disease and rare alleles using SNP arrays by relying on long stretches of genomic sharing that are identical by descent. We have developed an algorithm, DASH, which builds upon pairwise identical-by-descent shared segments to infer clusters of individuals likely to be sharing a single haplotype. DASH constructs a graph with nodes representing individuals and links on the basis of such segments spanning a locus and uses an iterative minimum cut algorithm to identify densely connected components. We have applied DASH to simulated data and diverse GWAS data sets by constructing haplotype clusters and testing them for association. In simulations we show this approach to be significantly more powerful than single-marker testing in an isolated population that is from Kosrae, Federated States of Micronesia and has abundant IBD, and we provide orthogonal information for rare, recent variants in the outbred Wellcome Trust Case-Control Consortium (WTCCC) data. In both cohorts, we identified a number of haplotype associations, five such loci in the WTCCC data and ten in the isolated, that were conditionally significant beyond any individual nearby markers. We have replicated one of these loci in an independent European cohort and identified putative structural changes in low-pass whole-genome sequence of the cluster carriers.

PMID:
21620352
PMCID:
PMC3113343
DOI:
10.1016/j.ajhg.2011.04.023
[Indexed for MEDLINE]
Free PMC Article

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