Open Access Open Badges Research article

Evaluation of two methods for computational HLA haplotypes inference using a real dataset

Bruno F Bettencourt12, Margarida R Santos12, Raquel N Fialho12, Ana R Couto12, Maria J Peixoto12, João P Pinheiro12, Hélder Spínola3, Marian G Mora4, Cristina Santos5, António Brehm3 and Jácome Bruges-Armas12*

Author Affiliations

1 Hospital Santo Espírito de Angra do Heroísmo, SEEBMO, Angra do Heroísmo, Azores, Portugal

2 Genetics & Arthritis Research Group (GARG), Institute for Molecular and Cell Biology (IBMC), University of Porto, Porto, Portugal

3 University of Madeira, Campus of Penteada, Funchal, Madeira, Portugal

4 Hospital Universitário de Canarias, Tenerife, Canarias, Spain

5 Center of Research in Natural Resources (CIRN) and Department of Biology, University of The Azores, Campus of Ponta Delgada, Ponta Delgada, Azores, Portugal

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BMC Bioinformatics 2008, 9:68  doi:10.1186/1471-2105-9-68

Published: 29 January 2008



HLA haplotype analysis has been used in population genetics and in the investigation of disease-susceptibility locus, due to its high polymorphism. Several methods for inferring haplotype genotypic data have been proposed, but it is unclear how accurate each of the methods is or which method is superior. The accuracy of two of the leading methods of computational haplotype inference – Expectation-Maximization algorithm based (implemented in Arlequin V3.0) and Bayesian algorithm based (implemented in PHASE V2.1.1) – was compared using a set of 122 HLA haplotypes (A-B-Cw-DQB1-DRB1) determined through direct counting. The accuracy was measured with the Mean Squared Error (MSE), Similarity Index (IF) and Haplotype Identification Index (IH).


None of the methods inferred all of the known haplotypes and some differences were observed in the accuracy of the two methods in terms of both haplotype determination and haplotype frequencies estimation. Working with haplotypes composed by low polymorphic sites, present in more than one individual, increased the confidence in the assignment of haplotypes and in the estimation of the haplotype frequencies generated by both programs.


The PHASE v2.1.1 implemented method had the best overall performance both in haplotype construction and frequency calculation, although the differences between the two methods were insubstantial. To our knowledge this was the first work aiming to test statistical methods using real haplotypic data from the HLA region.