Mapping Bias Overestimates Reference Allele Frequencies at the HLA Genes in the 1000 Genomes Project Phase I Data.

Détails

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Etat: Public
Version: Final published version
ID Serval
serval:BIB_0899CA1A59F7
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Mapping Bias Overestimates Reference Allele Frequencies at the HLA Genes in the 1000 Genomes Project Phase I Data.
Périodique
G3 Genes Genomes Genetics
Auteur(s)
Brandt D.Y., Aguiar V.R., Bitarello B.D., Nunes K., Goudet J., Meyer D.
ISSN
2160-1836 (Electronic)
ISSN-L
2160-1836
Statut éditorial
Publié
Date de publication
2015
Volume
5
Numéro
5
Pages
931-941
Langue
anglais
Résumé
Next-generation sequencing (NGS) technologies have become the standard for data generation in studies of population genomics, as the 1000 Genomes Project (1000G). However, these techniques are known to be problematic when applied to highly polymorphic genomic regions, such as the human leukocyte antigen (HLA) genes. Because accurate genotype calls and allele frequency estimations are crucial to population genomics analyses, it is important to assess the reliability of NGS data. Here, we evaluate the reliability of genotype calls and allele frequency estimates of the single-nucleotide polymorphisms (SNPs) reported by 1000G (phase I) at five HLA genes (HLA-A, -B, -C, -DRB1, and -DQB1). We take advantage of the availability of HLA Sanger sequencing of 930 of the 1092 1000G samples and use this as a gold standard to benchmark the 1000G data. We document that 18.6% of SNP genotype calls in HLA genes are incorrect and that allele frequencies are estimated with an error greater than ±0.1 at approximately 25% of the SNPs in HLA genes. We found a bias toward overestimation of reference allele frequency for the 1000G data, indicating mapping bias is an important cause of error in frequency estimation in this dataset. We provide a list of sites that have poor allele frequency estimates and discuss the outcomes of including those sites in different kinds of analyses. Because the HLA region is the most polymorphic in the human genome, our results provide insights into the challenges of using of NGS data at other genomic regions of high diversity.
Mots-clé
NGS, mapping bias, 1000 Genomes, HLA
Pubmed
Web of science
Open Access
Oui
Création de la notice
29/06/2015 12:46
Dernière modification de la notice
20/08/2019 12:30
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