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 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.
School of Biomedical Sciences, The University of Hong Kong, 21 Sassoon Road, Pokfulam, Hong Kong, Hong Kong.|Centre for Genomic Sciences, The University of Hong Kong, 5 Sassoon Road, Pokfulam, Hong Kong, Hong Kong.|Department of Cancer Genomics, LemonData Biotech (Shenzhen) Ltd., Shenzhen, China.
Yanhui
Y
Fan
School of Biomedical Sciences, The University of Hong Kong, 21 Sassoon Road, Pokfulam, Hong Kong, Hong Kong. songy@hku.hk.|Centre for Genomic Sciences, The University of Hong Kong, 5 Sassoon Road, Pokfulam, Hong Kong, Hong Kong. songy@hku.hk.
You-Qiang
YQ
Song
D000483:Alleles; D019295:Computational Biology / Q000379:methods*; D015894:Genome, Human; D060005:Genotyping Techniques; D006680:HLA Antigens / Q000235:genetics*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D016014:Linear Models; D016015:Logistic Models; D018895:Microsatellite Repeats; D008962:Models, Theoretical; D020641:Polymorphism, Single Nucleotide; D012984:Software
D006680:HLA Antigens
Association; HLA; Interaction; Multi-allelic