A multipoint method for detecting genotyping errors and mutations in sibling-pair linkage data - PubMed (original) (raw)

. 2000 Apr;66(4):1287-97.

doi: 10.1086/302861. Epub 2000 Mar 28.

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A multipoint method for detecting genotyping errors and mutations in sibling-pair linkage data

J A Douglas et al. Am J Hum Genet. 2000 Apr.

Abstract

The identification of genes contributing to complex diseases and quantitative traits requires genetic data of high fidelity, because undetected errors and mutations can profoundly affect linkage information. The recent emphasis on the use of the sibling-pair design eliminates or decreases the likelihood of detection of genotyping errors and marker mutations through apparent Mendelian incompatibilities or close double recombinants. In this article, we describe a hidden Markov method for detecting genotyping errors and mutations in multilocus linkage data. Specifically, we calculate the posterior probability of genotyping error or mutation for each sibling-pair-marker combination, conditional on all marker data and an assumed genotype-error rate. The method is designed for use with sibling-pair data when parental genotypes are unavailable. Through Monte Carlo simulation, we explore the effects of map density, marker-allele frequencies, marker position, and genotype-error rate on the accuracy of our error-detection method. In addition, we examine the impact of genotyping errors and error detection and correction on multipoint linkage information. We illustrate that even moderate error rates can result in substantial loss of linkage information, given efforts to fine-map a putative disease locus. Although simulations suggest that our method detects </=50% of genotyping errors, it generally flags those errors that have the largest impact on linkage results. For high-resolution genetic maps, removal of the errors identified by our method restores most or nearly all the lost linkage information and can be accomplished without generating false evidence for linkage by removing incorrectly identified errors.

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Figures

Figure 1

Figure 1

True-positive rate versus false-positive rate, assuming a genotype-error rate of .01, markers with four equally frequent alleles, and a 100-cM map with markers equally spaced at 1-, 2-, 3-, or 5-cM intervals. True-positive rates were based on introduction of random genotype error for at least one member of the sibling pair at the marker in the middle of the map.

Figure 2

Figure 2

True-positive rate as a function of marker distance from the end of the map, on the assumption of a true genotype-error rate of .01, markers with four equally frequent alleles, and a 100-cM map with markers equally spaced at 1-, 2-, 3-, or 5-cM intervals. True-positive rates were based on introduction of random genotype error for at least one member of the sibling pair at the positioned marker. The false-positive rate was fixed at .001.

Figure 3

Figure 3

Impact of genotyping errors and error detection on linkage information, as measured by maximum LOD score. Linkage data were simulated for 400 sibling pairs on the assumption of a recurrence-risk ratio

λ=1.25

. Results shown are based on a 100-cM map, markers with four equally frequent alleles equally spaced at 1-cM intervals, and a disease locus placed at 50.5 cM. Random genotype errors were introduced in each sibling at each marker with probability equal to the genotype-error rate of 1%. Error removal (— —) gives linkage results after removing sibling-pair-marker combinations with high posterior error probabilities, on the assumption of a false-positive rate of .001.

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References

Electronic-Database Information

    1. ASPEX (Affected Sib Pairs EXclusion Map) version 2.2, ftp://lahmed.stanford.edu/pub/aspex/index.html
    1. SIBMED program, <http://www. sph.umich.edu/group/statgen/software>

References

    1. Baum LE (1972) An inequality and associated maximization technique in statistical estimation for probabilistic functions of Markov processes. Inequalities 3:11–18
    1. Brzustowicz LM, Merette C, Xie X, Townsend L, Gilliam TC, Ott J (1993) Molecular and statistical approaches to the detection and correction of errors in genotype databases. Am J Hum Genet 53:1137–1145 - PMC - PubMed
    1. Buetow KH (1991) Influence of aberrant observations on high-resolution linkage analysis outcomes. Am J Hum Genet 49:985–994 - PMC - PubMed
    1. Douglas J, Boehnke M, Lange K (1998) Identifying marker genotyping errors and mutations in sibling-pair linkage data. Am J Hum Genet Suppl 63:A1661 - PMC - PubMed
    1. Dracopoli NC, O’Connell P, Elsner TI, Lalouel J-M, White RL, Buetow K, Nishimura DY, et al (1991) The CEPH consortium linkage map of human chromosome 1. Genomics 9:686–700 - PubMed

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