Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation

Bogdan Pasaniuc*, Sriram Sankararaman, Dara G. Torgerson, Christopher Gignoux, Noah Zaitlen, Celeste Eng, William Rodriguez-Cintron, Rocio Chapela, Jean G. Ford, Pedro C. Avila, Jose Rodriguez-Santana, Gary K. Chen, Loic Le Marchand, Brian Henderson, David Reich, Christopher A. Haiman, Esteban Gonzàlez Burchard, Eran Halperin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Motivation: Local ancestry analysis of genotype data from recently admixed populations (e.g. Latinos, African Americans) provides key insights into population history and disease genetics. Although methods for local ancestry inference have been extensively validated in simulations (under many unrealistic assumptions), no empirical study of local ancestry accuracy in Latinos exists to date. Hence, interpreting findings that rely on local ancestry in Latinos is challenging.Results: Here, we use 489 nuclear families from the mainland USA, Puerto Rico and Mexico in conjunction with 3204 unrelated Latinos from the Multiethnic Cohort study to provide the first empirical characterization of local ancestry inference accuracy in Latinos. Our approach for identifying errors does not rely on simulations but on the observation that local ancestry in families follows Mendelian inheritance. We measure the rate of local ancestry assignments that lead to Mendelian inconsistencies in local ancestry in trios (MILANC), which provides a lower bound on errors in the local ancestry estimates. We show that MILANC rates observed in simulations underestimate the rate observed in real data, and that MILANC varies substantially across the genome. Second, across a wide range of methods, we observe that loci with large deviations in local ancestry also show enrichment in MILANC rates. Therefore, local ancestry estimates at such loci should be interpreted with caution. Finally, we reconstruct ancestral haplotype panels to be used as reference panels in local ancestry inference and show that ancestry inference is significantly improved by incoroprating these reference panels.

Original languageEnglish (US)
Pages (from-to)1407-1415
Number of pages9
JournalBioinformatics
Volume29
Issue number11
DOIs
StatePublished - Jun 1 2013

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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