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全基因组关联研究汇总统计数据的宝库：方法与工具的系统综述

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

作者信息

Kontou Panagiota I, Bagos Pantelis G

机构信息

Department of Mathematics, University of Thessaly, 35131, Lamia, Greece.

Department of Computer Science and Biomedical Informatics, University of Thessaly, 35131, Lamia, Greece.

出版信息

BioData Min. 2024 Sep 5;17(1):31. doi: 10.1186/s13040-024-00385-x.

DOI:10.1186/s13040-024-00385-x
PMID:39238044
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11375927/
Abstract

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.

摘要

全基因组关联研究（GWAS）彻底改变了我们对复杂性状和疾病遗传结构的理解。GWAS汇总统计数据已成为各种遗传分析的重要工具，包括荟萃分析、精细定位和风险预测。然而，GWAS汇总统计数据的数量不断增加，以及可用于分析的软件工具的多样性，可能使研究人员难以选择最适合其特定需求的工具。本系统综述旨在全面概述目前可用于GWAS汇总统计数据分析的软件工具和数据库。我们进行了全面的文献检索，以确定相关的软件工具和数据库。我们根据工具和数据库的功能对其进行分类，包括数据管理、质量控制、单性状分析和多性状分析。我们还根据工具和数据库的特点、局限性和用户友好性进行了比较。我们的综述共确定了305个专门用于GWAS汇总统计数据的功能正常的软件工具和数据库，每个工具和数据库都有独特的优势和局限性。我们描述了每个工具和数据库的关键特性，包括它们的输入/输出格式、数据类型和计算要求。我们还讨论了每个工具在不同研究场景中的总体可用性和适用性。对于有兴趣使用GWAS汇总统计数据来研究复杂性状和疾病遗传基础的研究人员来说，这一全面综述将是一个宝贵的资源。通过详细概述可用的工具和数据库，我们旨在促进明智的工具选择，并最大限度地提高GWAS汇总统计数据分析的有效性。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/11375927/3b842c6a4f8f/13040_2024_385_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/11375927/2eef49498a85/13040_2024_385_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/11375927/bf2874e2c468/13040_2024_385_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/11375927/43355bbe881b/13040_2024_385_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e1a/11375927/5bfd781d7f7c/13040_2024_385_Fig9_HTML.jpg

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