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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Evaluation of computational methods for the reconstruction of HLA haplotypes

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Author(s):
Castelli, E. C. [1] ; Mendes-Junior, C. T. [2] ; Veiga-Castelli, L. C. [3] ; Pereira, N. F. [4] ; Petzl-Erler, M. L. [5] ; Donadi, E. A. [1]
Total Authors: 6
Affiliation:
[1] Univ Sao Paulo, Fac Med Ribeirao Preto, Dept Clin Med, BR-14049900 Ribeirao Preto, SP - Brazil
[2] Univ Sao Paulo, Fac Filosofia Ciencias & Letras Ribeirao Preto, Dept Quim, BR-14049900 Ribeirao Preto, SP - Brazil
[3] Univ Sao Paulo, Fac Med Ribeirao Preto, Dept Genet, BR-14049900 Ribeirao Preto, SP - Brazil
[4] Univ Fed Parana, Hosp Clin, Immunogenet Lab, BR-80060000 Curitiba, Parana - Brazil
[5] Univ Fed Parana, Dept Genet, Lab Genet Mol Humana, BR-80060000 Curitiba, Parana - Brazil
Total Affiliations: 5
Document type: Journal article
Source: TISSUE ANTIGENS; v. 76, n. 6, p. 459-466, DEC 2010.
Web of Science Citations: 17
Abstract

Human leukocyte antigen (HLA) haplotypes are frequently evaluated for population history inferences and association studies. However, the available typing techniques for the main HLA loci usually do not allow the determination of the allele phase and the constitution of a haplotype, which may be obtained by a very time-consuming and expensive family-based segregation study. Without the family-based study, computational inference by probabilistic models is necessary to obtain haplotypes. Several authors have used the expectation-maximization (EM) algorithm to determine HLA haplotypes, but high levels of erroneous inferences are expected because of the genetic distance among the main HLA loci and the presence of several recombination hotspots. In order to evaluate the efficiency of computational inference methods, 763 unrelated individuals stratified into three different datasets had their haplotypes manually defined in a family-based study of HLA-A, -B, -DRB1 and -DQB1 segregation, and these haplotypes were compared with the data obtained by the following three methods: the Expectation-Maximization (EM) and Excoffier-Laval-Balding (ELB) algorithms using the arlequin 3.11 software, and the PHASE method. When comparing the methods, we observed that all algorithms showed a poor performance for haplotype reconstruction with distant loci, estimating incorrect haplotypes for 38%-57% of the samples considering all algorithms and datasets. We suggest that computational haplotype inferences involving low-resolution HLA-A, HLA-B, HLA-DRB1 and HLA-DQB1 haplotypes should be considered with caution. (AU)