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PyHLA:用于检测HLA等位基因与疾病之间关联的测试。

PyHLA: tests for the association between HLA alleles and diseases.

作者信息

Fan Yanhui, Song You-Qiang

机构信息

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.

出版信息

BMC Bioinformatics. 2017 Feb 6;18(1):90. doi: 10.1186/s12859-017-1496-0.

Abstract

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.

摘要

背景

最近,已经设计了几种利用单核苷酸多态性(SNP)阵列和下一代测序(NGS)数据进行人类白细胞抗原(HLA)分型的工具。这些工具为鉴定HLA类型提供了高通量且具有成本效益的方法。因此,非常需要用于下游关联分析的工具。尽管已经设计了几种用于多等位基因标记关联分析的工具,但它们仅针对微卫星标记设计,并且随着数据量的增加扩展性不佳,或者它们是针对大规模数据设计的,但提供的测试数量有限。

结果

我们开发了一个名为PyHLA的Python软件包,它实现了几种HLA关联分析方法,以填补这一空白。PyHLA是一个量身定制、易于使用且灵活的工具,专门为从全基因组基因分型和NGS数据推断出的HLA类型的关联分析而设计。PyHLA提供了用于关联分析、纯合性测试以及HLA等位基因与疾病之间相互作用测试的功能。还实现了蒙特卡洛置换和几种多重检验校正方法。

结论

PyHLA为HLA分析提供了一个方便且强大的工具。现有方法已在PyHLA中集成,并且添加了所需的方法。此外,PyHLA适用于小样本和大样本,并且可以在不同平台的个人计算机上及时完成分析。PyHLA是用Python实现的。PyHLA是一个根据GPLv2许可分发的免费开源软件。源代码、教程和示例可在https://github.com/felixfan/PyHLA获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87c7/5292802/dd3287a7275a/12859_2017_1496_Fig1_HTML.jpg

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