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Derivation of HLA types from shotgun sequence datasets
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 prod...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3580435/ https://www.ncbi.nlm.nih.gov/pubmed/23228053 http://dx.doi.org/10.1186/gm396 |
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author | Warren, René L Choe, Gina Freeman, Douglas J Castellarin, Mauro Munro, Sarah Moore, Richard Holt, Robert A |
author_facet | Warren, René L Choe, Gina Freeman, Douglas J Castellarin, Mauro Munro, Sarah Moore, Richard Holt, Robert A |
author_sort | Warren, René L |
collection | PubMed |
description | 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 (http://www.bcgsc.ca/platform/bioinfo/software/hlaminer). 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. |
format | Online Article Text |
id | pubmed-3580435 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35804352013-03-04 Derivation of HLA types from shotgun sequence datasets Warren, René L Choe, Gina Freeman, Douglas J Castellarin, Mauro Munro, Sarah Moore, Richard Holt, Robert A Genome Med Method 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 (http://www.bcgsc.ca/platform/bioinfo/software/hlaminer). 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. BioMed Central 2012-12-10 /pmc/articles/PMC3580435/ /pubmed/23228053 http://dx.doi.org/10.1186/gm396 Text en Copyright ©2012 Warren et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Method Warren, René L Choe, Gina Freeman, Douglas J Castellarin, Mauro Munro, Sarah Moore, Richard Holt, Robert A Derivation of HLA types from shotgun sequence datasets |
title | Derivation of HLA types from shotgun sequence datasets |
title_full | Derivation of HLA types from shotgun sequence datasets |
title_fullStr | Derivation of HLA types from shotgun sequence datasets |
title_full_unstemmed | Derivation of HLA types from shotgun sequence datasets |
title_short | Derivation of HLA types from shotgun sequence datasets |
title_sort | derivation of hla types from shotgun sequence datasets |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3580435/ https://www.ncbi.nlm.nih.gov/pubmed/23228053 http://dx.doi.org/10.1186/gm396 |
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