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PyHLA: tests for the association between HLA alleles and diseases

BACKGROUND: Recently, several tools have been designed for human leukocyte antigen (HLA) typing using single nucleotide polymorphism (SNP) array and next-generation sequencing (NGS) data. These tools provide high-throughput and cost-effective approaches for identifying HLA types. Therefore, tools fo...

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Autores principales: Fan, Yanhui, Song, You-Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5292802/
https://www.ncbi.nlm.nih.gov/pubmed/28166716
http://dx.doi.org/10.1186/s12859-017-1496-0
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author Fan, Yanhui
Song, You-Qiang
author_facet Fan, Yanhui
Song, You-Qiang
author_sort Fan, Yanhui
collection PubMed
description BACKGROUND: Recently, several tools have been designed for human leukocyte antigen (HLA) typing using single nucleotide polymorphism (SNP) array and next-generation sequencing (NGS) data. These tools provide high-throughput and cost-effective approaches for identifying HLA types. Therefore, tools for downstream association analysis are highly desirable. Although several tools have been designed for multi-allelic marker association analysis, they were designed only for microsatellite markers and do not scale well with increasing data volumes, or they were designed for large-scale data but provided a limited number of tests. RESULTS: We have developed a Python package called PyHLA, which implements several methods for HLA association analysis, to fill the gap. PyHLA is a tailor-made, easy to use, and flexible tool designed specifically for the association analysis of the HLA types imputed from genome-wide genotyping and NGS data. PyHLA provides functions for association analysis, zygosity tests, and interaction tests between HLA alleles and diseases. Monte Carlo permutation and several methods for multiple testing corrections have also been implemented. CONCLUSIONS: PyHLA provides a convenient and powerful tool for HLA analysis. Existing methods have been integrated and desired methods have been added in PyHLA. Furthermore, PyHLA is applicable to small and large sample sizes and can finish the analysis in a timely manner on a personal computer with different platforms. PyHLA is implemented in Python. PyHLA is a free, open source software distributed under the GPLv2 license. The source code, tutorial, and examples are available at https://github.com/felixfan/PyHLA.
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spelling pubmed-52928022017-02-10 PyHLA: tests for the association between HLA alleles and diseases Fan, Yanhui Song, You-Qiang BMC Bioinformatics Software BACKGROUND: Recently, several tools have been designed for human leukocyte antigen (HLA) typing using single nucleotide polymorphism (SNP) array and next-generation sequencing (NGS) data. These tools provide high-throughput and cost-effective approaches for identifying HLA types. Therefore, tools for downstream association analysis are highly desirable. Although several tools have been designed for multi-allelic marker association analysis, they were designed only for microsatellite markers and do not scale well with increasing data volumes, or they were designed for large-scale data but provided a limited number of tests. RESULTS: We have developed a Python package called PyHLA, which implements several methods for HLA association analysis, to fill the gap. PyHLA is a tailor-made, easy to use, and flexible tool designed specifically for the association analysis of the HLA types imputed from genome-wide genotyping and NGS data. PyHLA provides functions for association analysis, zygosity tests, and interaction tests between HLA alleles and diseases. Monte Carlo permutation and several methods for multiple testing corrections have also been implemented. CONCLUSIONS: PyHLA provides a convenient and powerful tool for HLA analysis. Existing methods have been integrated and desired methods have been added in PyHLA. Furthermore, PyHLA is applicable to small and large sample sizes and can finish the analysis in a timely manner on a personal computer with different platforms. PyHLA is implemented in Python. PyHLA is a free, open source software distributed under the GPLv2 license. The source code, tutorial, and examples are available at https://github.com/felixfan/PyHLA. BioMed Central 2017-02-06 /pmc/articles/PMC5292802/ /pubmed/28166716 http://dx.doi.org/10.1186/s12859-017-1496-0 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Fan, Yanhui
Song, You-Qiang
PyHLA: tests for the association between HLA alleles and diseases
title PyHLA: tests for the association between HLA alleles and diseases
title_full PyHLA: tests for the association between HLA alleles and diseases
title_fullStr PyHLA: tests for the association between HLA alleles and diseases
title_full_unstemmed PyHLA: tests for the association between HLA alleles and diseases
title_short PyHLA: tests for the association between HLA alleles and diseases
title_sort pyhla: tests for the association between hla alleles and diseases
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5292802/
https://www.ncbi.nlm.nih.gov/pubmed/28166716
http://dx.doi.org/10.1186/s12859-017-1496-0
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