A note on statistical method for genotype calling of high-throughput single-nucleotide polymorphism arrays

Jiaqi Yang, Wei Zhang and Baolin Wu

Journal of Applied Statistics, 2013, vol. 40, issue 6, 1372-1381

Abstract: We study the genotype calling algorithms for the high-throughput single-nucleotide polymorphism (SNP) arrays. Building upon the novel SNP-robust multi-chip average preprocessing approach and the state-of-the-art corrected robust linear model with Mahalanobis distance (CRLMM) approach for genotype calling, we propose a simple modification to better model and combine the information across multiple SNPs with empirical Bayes modeling, which could often significantly improve the genotype calling of CRLMM. Through applications to the HapMap Trio data set and a non-HapMap test set of high quality SNP chips, we illustrate the competitive performance of the proposed method.

Date: 2013
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DOI: 10.1080/02664763.2013.785499

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