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Article

PGA: post-GWAS analysis for disease gene identification.

Bioinformatics (Oxford, England) - 15 May 2018

Lin Jhih-Rong, Jaroslawicz Daniel, Cai Ying, Zhang Quanwei, Wang Zhen, Zhang Zhengdong D

Abstract excerpt

Summary: Although the genome-wide association study (GWAS) is a powerful method to identify disease-associated variants, it does not directly address the biological mechanisms underlying such genetic association signals. Here, we present PGA, a Perl- and Java-based program for post-GWAS analysis that predicts likely disease genes given a list of GWAS-reported variants. Designed with a command line interface, PGA...

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Identifiers

PMID: 29300829
DOI: 10.1093/bioinformatics/btx845
PMCID: PMC5946835

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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