Evaluation of label dependency for the prediction of HLA genes

Vanja Paunić, Michael Steinbach, Abeer Madbouly, Vipin Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The Human Leukocyte Antigen (HLA) gene system plays a crucial role in hematopoietic stem cell transplantation, where patients and donors are matched with respect to their HLA genes in order to maximize the chances of a successful transplant. It is the most polymorphic region of the human genome with some of the strongest associations with autoimmune, infectious, and inammatory diseases. The availability of HLA data is, therefore, of high importance to clinicians and researchers. However, due to its high polymorphism, obtaining it is time- And cost-prohibitive. We previously described a method for the prediction of HLA genes from widely available Single Nucleotide Polymorphism (SNP) data. In this paper we show that using HLA gene dependency information improves prediction performance on multiple real-world data sets. More specifically, we propose and evaluate different approaches for integrating HLA gene dependency into the prediction process. The results from experiments on two real data sets show that adding dependency information is a valuable asset for HLA gene prediction, particularly for smaller data sets.

Original languageEnglish (US)
Title of host publication2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013
Pages296-305
Number of pages10
DOIs
StatePublished - Nov 28 2013
Event2013 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013 - Wshington, DC, United States
Duration: Sep 22 2013Sep 25 2013

Publication series

Name2013 ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013

Other

Other2013 4th ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics, ACM-BCB 2013
Country/TerritoryUnited States
CityWshington, DC
Period9/22/139/25/13

Keywords

  • HLA imputation
  • Human leukocyte antigen
  • Label dependency
  • Multi-label prediction
  • SNPs

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