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Derivation of HLA types from shotgun sequence datasets

René L Warren1, Gina Choe1, Douglas J Freeman1, Mauro Castellarin1, Sarah Munro1, Richard Moore1 and Robert A Holt12*

Author Affiliations

1 BC Cancer Agency, Michael Smith Genome Sciences Centre, Vancouver, British Columbia V5Z 1L3, Canada

2 Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada

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Genome Medicine 2012, 4:95  doi:10.1186/gm396

Published: 10 December 2012


The human leukocyte antigen (HLA) is key to many aspects of human physiology and medicine. All current sequence-based HLA typing methodologies are targeted approaches requiring the amplification of specific HLA gene segments. Whole genome, exome and transcriptome shotgun sequencing can generate prodigious data but due to the complexity of HLA loci these data have not been immediately informative regarding HLA genotype. We describe HLAminer, a computational method for identifying HLA alleles directly from shotgun sequence datasets ( webcite). This approach circumvents the additional time and cost of generating HLA-specific data and capitalizes on the increasing accessibility and affordability of massively parallel sequencing.