期刊
BIOINFORMATICS
卷 28, 期 10, 页码 1359-1367出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bts144
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资金
- Edmond J. Safra Center for Bioinformatics at Tel Aviv University
- Israeli Science Foundation [04514831]
- National Institutes of Health [R01 HG006399]
Results: To address these challenges we introduce here methods for local ancestry inference which leverage the structure of linkage disequilibrium in the ancestral population (LAMP-LD), and incorporate the constraint of Mendelian segregation when inferring local ancestry in nuclear family trios (LAMP-HAP). Our algorithms uniquely combine hidden Markov models (HMMs) of haplotype diversity within a novel window-based framework to achieve superior accuracy as compared with published methods. Further, unlike previous methods, the structure of our HMM does not depend on the number of reference haplotypes but on a fixed constant, and it is thereby capable of utilizing large datasets while remaining highly efficient and robust to over-fitting. Through simulations and analysis of real data from 489 nuclear trio families from the mainland US, Puerto Rico and Mexico, we demonstrate that our methods achieve superior accuracy compared with published methods for local ancestry inference in Latinos.
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