The goldmine of GWAS summary statistics: a systematic review of methods and tools

被引:3
作者
Kontou, Panagiota I. [1 ]
Bagos, Pantelis G. [2 ]
机构
[1] Univ Thessaly, Dept Math, Lamia 35131, Greece
[2] Univ Thessaly, Dept Comp Sci & Biomed Informat, Lamia 35131, Greece
来源
BIODATA MINING | 2024年 / 17卷 / 01期
关键词
GWAS; Summary statistics; Software; database; systematic review; GENOME-WIDE ASSOCIATION; GENE SET ANALYSIS; LD SCORE REGRESSION; MENDELIAN RANDOMIZATION; COMPLEX TRAITS; WEB SERVER; DIRECT IMPUTATION; SNP HERITABILITY; QUALITY-CONTROL; R PACKAGE;
D O I
10.1186/s13040-024-00385-x
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Genome-wide association studies (GWAS) have revolutionized our understanding of the genetic architecture of complex traits and diseases. GWAS summary statistics have become essential tools for various genetic analyses, including meta-analysis, fine-mapping, and risk prediction. However, the increasing number of GWAS summary statistics and the diversity of software tools available for their analysis can make it challenging for researchers to select the most appropriate tools for their specific needs. This systematic review aims to provide a comprehensive overview of the currently available software tools and databases for GWAS summary statistics analysis. We conducted a comprehensive literature search to identify relevant software tools and databases. We categorized the tools and databases by their functionality, including data management, quality control, single-trait analysis, and multiple-trait analysis. We also compared the tools and databases based on their features, limitations, and user-friendliness. Our review identified a total of 305 functioning software tools and databases dedicated to GWAS summary statistics, each with unique strengths and limitations. We provide descriptions of the key features of each tool and database, including their input/output formats, data types, and computational requirements. We also discuss the overall usability and applicability of each tool for different research scenarios. This comprehensive review will serve as a valuable resource for researchers who are interested in using GWAS summary statistics to investigate the genetic basis of complex traits and diseases. By providing a detailed overview of the available tools and databases, we aim to facilitate informed tool selection and maximize the effectiveness of GWAS summary statistics analysis.
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页数:40
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