Statistical imputation of classical HLA alleles in case-control studies has become established as a valuable tool for identifying and fine-mapping signals of disease association in the MHC. Imputation into diverse populations has, however, remained challenging, mainly because of the additional haplotypic heterogeneity introduced by combining reference panels of different sources. We present an ...

We assessed a scenario designed to mimic the imputation of full genome sequence data in White layer chickens, genotyped at medium (60K) density. Factors affecting accuracy were the size of the reference population, the level of the relationship between the reference and test populations and minor allele frequency of the SNP being imputed. Genotype imputation based on 22 or 62 carefully selected...

Genome-wide association studies generate very large datasets that require scalable analysis algorithms. In this report we describe the GEDI software package, which implements efficient algorithms for performing several common tasks in the analysis of population genotype data, including genotype error detection and correction, imputation of both randomly missing and untyped genotypes, and genoty...

This paper addresses the issue of exact-test based statistical inference for Hardy-Weinberg equilibrium in the presence of missing genotype data. Missing genotypes often are discarded when markers are tested for Hardy-Weinberg equilibrium, which can lead to bias in the statistical inference about equilibrium. Single and multiple imputation can improve inference on equilibrium. We develop tests ...

Abstract Genotypes generated from common single nucleotide polymorphisms (SNP) chips have been the sole source of genomic information for current beef cattle genetic evaluations. More recently, development low-pass whole-genome sequencing (LPS) followed by imputation to full sequence and variant calls has provided an alternative option generate genotypes inclusion into The objective this study ...

MOTIVATION Typical high-throughput genotyping techniques produce numerous missing calls that confound subsequent analyses, such as disease association studies. Common remedies for this problem include removing affected markers and/or samples or, otherwise, imputing the missing data. On small marker sets imputation is frequently based on a vote of the K-nearest-neighbor (KNN) haplotypes, but thi...

High coverage whole genome sequencing provides near complete information about genetic variation. However, other technologies can be more efficient in some settings by (a) reducing redundant coverage within samples and (b) exploiting patterns of genetic variation across samples. To characterize as many samples as possible, many genetic studies therefore employ lower coverage sequencing or SNP a...