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PMID: 18971310 Published · ppublish English Comparative Study Evaluation Study Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Whole population, genome-wide mapping of hidden relatedness.

Genome research ·Vol. 19 ·No. 2 ·2009-02-00 ·Pages 318-26

Gusev A, Lowe JK, Stoffel M, Daly MJ, Altshuler D, Breslow JL, Friedman JM, Pe'er I

Abstract

We present GERMLINE, a robust algorithm for identifying segmental sharing indicative of recent common ancestry between pairs of individuals. Unlike methods with comparable objectives, GERMLINE scales linearly with the number of samples, enabling analysis of whole-genome data in large cohorts. Our approach is based on a dictionary of haplotypes that is used to efficiently discover short exact matches between individuals. We then expand these matches using dynamic programming to identify long, nearly identical segmental sharing that is indicative of relatedness. We use GERMLINE to comprehensively survey hidden relatedness both in the HapMap as well as in a densely typed island population of 3000 individuals. We verify that GERMLINE is in concordance with other methods when they can process the data, and also facilitates analysis of larger scale studies. We bolster these results by demonstrating novel applications of precise analysis of hidden relatedness for (1) identification and resolution of phasing errors and (2) exposing polymorphic deletions that are otherwise challenging to detect. This finding is supported by concordance of detected deletions with other evidence from independent databases and statistical analyses of fluorescence intensity not used by GERMLINE.

MeSH Terms
Algorithms Chromosome Mapping/methods Consanguinity Family Relations Genetics, Population/methods Haplotypes Humans Inheritance Patterns/genetics Models, Genetic Phylogeny Polymorphism, Single Nucleotide Sensitivity and Specificity
Authors & Affiliations
8 authors, click to expand affiliations / ORCID
Gusev Alexander
Department of Computer Science, Columbia University, New York, New York 10027, USA. gusev@cs.columbia.edu
Lowe Jennifer K
Stoffel Markus
Daly Mark J
Altshuler David
Breslow Jan L
Friedman Jeffrey M
Pe'er Itsik
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Article Info
Journal
Genome research
Abbr.
Genome Res
ISSN
1088-9051
DOI
10.1101/gr.081398.108
Email
gusev@cs.columbia.edu
Published
2009-02-00
Epub
2008-00-29
Pages
318-26
Language
English
Region
United States
NLM ID
9518021
PMCID
PMC2652213
Subset
IM
Grants
NIDDK NIH HHS · 5R01 DK60089 · United States
NIDDK NIH HHS · R01 DK060089 · United States
NCI NIH HHS · U54 CA121852 · United States
Howard Hughes Medical Institute · United States
NCI NIH HHS · 5 U54 CA121852 · United States
External Links
PubMed source DOI: 10.1101/gr.081398.108 PMC Full Text View journal details
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