MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes
Open accessAbstract
Genome‐wide association studies (GWAS) can identify common alleles that contribute to complex disease susceptibility. Despite the large number of SNPs assessed in each study, the effects of most common SNPs must be evaluated indirectly using either genotyped markers or haplotypes thereof as proxies. We have previously implemented a computationally efficient Markov Chain framework for genotype imputation and haplotyping in the freely available MaCH software package. The approach describes sampled chromosomes as mosaics of each other and uses available genotype and shotgun sequence data to estimate unobserved genotypes and haplotypes, together with useful measures of the quality of these estimates. Our approach is already widely used to facilitate comparison of results across studies as well as meta‐analyses of GWAS. Here, we use simulations and experimental genotypes to evaluate its accuracy and utility, considering choices of genotyping panels, reference panel configurations, and designs where genotyping is replaced with shotgun sequencing. Importantly, we show that genotype imputation not only facilitates cross study analyses but also increases power of genetic association studies. We show that genotype imputation of common variants using HapMap haplotypes as a reference is very accurate using either genome‐wide SNP data or smaller amounts of data typical in fine‐mapping studies. Furthermore, we show the approach is applicable in a variety of populations. Finally, we illustrate how association analyses of unobserved variants will benefit from ongoing advances such as larger HapMap reference panels and whole genome shotgun sequencing technologies.Genet. Epidemiol. 34: 816‐834, 2010. © 2010 Wiley‐Liss, Inc.
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Each study was subject to GWAS quality control filters customized taking into account study-specific features and standardized to the HapMap reference panel and statistical genotype imputation.
“Each study was first subject to GWAS quality control filters (customized taking into account study specific features21 as detailed in Supplementary Table 2) and standardized to the HapMap reference panel and statistical genotype imputation22–25.”
From Seven new loci associated with age-related macular degeneration (2013) · cites this paper as [25]
Imputed genotypes were inferred with MaCH 1.0.16 using combined CEU and YRI haplotypes as reference; we report SNPs whose predicted R∧2 between true and imputed genotypes >0.80.
“Imputed genotypes were inferred with the MaCH 1.0.16 package [52] using combined CEU and YRI haplotypes as reference; we report SNPs whose predicted R∧2 between true and imputed genotypes >0.80.”
From Genetic Architecture of Skin and Eye Color in an African-European Admixed Population (2013) · cites this paper as [52]
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- Authors
- Li, Y., Willer, C. J., Ding, J., Scheet, P., & Abecasis, G. R.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- University of Michigan (US)
- The University of Texas MD Anderson Cancer Center (US)
- Corresponding author
- Abecasis, Gonçalo R.
- Venue
- Genetic Epidemiology
- Publisher
- Wiley
- Published
- 2010-11-05
- Volume
- 34
- Issue
- 8
- Pages
- 816-834
- ISSN
- 0741-0395 (ISSN-L)
- 1098-2272
- PMC
- PMC3175618
- OpenAlex
- W2166501262
- Cited by
- 1,843
- References
- 55
- Citations by year
- 2026: 13 · 2025: 26 · 2024: 23 · 2023: 33 · 2022: 51 · 2021: 72 · 2020: 84 · 2019: 114 · 2018: 125 · 2017: 138 · 2016: 160 · 2015: 221 · 2014: 222 · 2013: 238 · 2012: 216
- FWCI
- 99.72
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Genetic Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- Deep Blue (University of Michigan) (submittedVersion)
- Funders
- National Institutes of Health (5k99hl094535-02)
- National Heart, Lung, and Blood Institute (U01HL084729, K99-HL094535)
- National Institute of Mental Health (R01MH084698)
- National Human Genome Research Institute (R01HG002651, U01HG005214, RC2HG005552)
- National Cancer Institute (R01CA082659)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- Mach, genotype imputation, haplotyping, Markov chains, genome-wide association study, shotgun sequencing, common genetic variants, fine mapping
- MeSH terms
- Alleles, Base Sequence, Chromosomes, Genetic Markers, Genotype, Haplotypes, Humans, Markov Chains, Sensitivity and Specificity, Software, Genome, Human, Polymorphism, Single Nucleotide, Genome-Wide Association Study
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