webTWAS 2.0: update platform for identifying complex disease susceptibility genes through transcriptome-wide association study.

IF 16.6 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Nucleic Acids Research Pub Date : 2024-11-11 DOI:10.1093/nar/gkae1022
Chen Cao, Mengting Shao, Jianhua Wang, Zhenghui Li, Haoran Chen, Tianyi You, Mulin Jun Li, Yijie Ding, Quan Zou
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Abstract

Transcriptome-wide association study (TWAS) has successfully identified numerous complex disease susceptibility genes in the post-genome-wide association study (GWAS) era. Over the past 3 years, the focus of TWAS algorithms has shifted from merely identifying associations to understanding how single nucleotide polymorphisms (SNPs) regulate gene expression, with a growing emphasis on incorporating fine-mapping techniques. Additionally, the rapid increase in GWAS summary statistics, driven largely by the UK Biobank and other consortia, has made it essential to update our webTWAS resource. To address these challenges and meet the growing needs of researchers, we developed webTWAS 2.0, an updated platform for identifying susceptibility genes for human complex diseases using TWAS. Additionally, webTWAS 2.0 provides an online TWAS analysis tool that simplifies conducting TWAS analyses. The updated resource includes 7247 GWAS summary statistics covering 1588 complex human diseases from 192 publications. It also incorporates multiple TWAS methods, such as sTF-TWAS, 3'aTWAS and GIFT, along with an updated interactive visualization tool that allows users to easily explore significant associations across different methods. Other upgrades include a personalized online analysis tool for user-submitted GWAS data and a refined search function that makes it easier to identify relevant associations and meet diverse user needs more efficiently. webTWAS 2.0 is freely accessible at http://www.webtwas.net.

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webTWAS 2.0:通过全转录组关联研究确定复杂疾病易感基因的更新平台。
在后全基因组关联研究(GWAS)时代,转录组关联研究(TWAS)已成功鉴定出许多复杂疾病的易感基因。在过去 3 年中,TWAS 算法的重点已从单纯的关联鉴定转向了解单核苷酸多态性(SNPs)如何调控基因表达,并越来越重视结合精细图谱技术。此外,主要由英国生物库(UK Biobank)和其他联盟推动的 GWAS 统计摘要的快速增长,使得我们必须更新我们的 webTWAS 资源。为了应对这些挑战并满足研究人员日益增长的需求,我们开发了 webTWAS 2.0,这是一个利用 TWAS 鉴定人类复杂疾病易感基因的最新平台。此外,webTWAS 2.0 还提供了一个在线 TWAS 分析工具,简化了 TWAS 分析的操作。更新后的资源包括 7247 个 GWAS 统计摘要,涵盖 192 个出版物中的 1588 种人类复杂疾病。它还整合了多种 TWAS 方法,如 sTF-TWAS、3'aTWAS 和 GIFT,以及更新的交互式可视化工具,使用户可以轻松探索不同方法之间的显著关联。其他升级还包括针对用户提交的 GWAS 数据的个性化在线分析工具和经过改进的搜索功能,从而更容易识别相关关联,更有效地满足不同用户的需求。webTWAS 2.0 可在 http://www.webtwas.net 免费访问。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nucleic Acids Research
Nucleic Acids Research 生物-生化与分子生物学
CiteScore
27.10
自引率
4.70%
发文量
1057
审稿时长
2 months
期刊介绍: Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.
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