Editome Disease Knowledgebase v2.0: an updated resource of editome-disease associations through literature curation and integrative analysis.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Bioinformatics advances Pub Date : 2025-01-25 eCollection Date: 2025-01-01 DOI:10.1093/bioadv/vbaf012

Tongtong Zhu, Yuan Chu, Guangyi Niu, Rong Pan, Ming Chen, Yuanyuan Cheng, Yuansheng Zhang, Zhao Li, Shuai Jiang, Lili Hao, Dong Zou, Tianyi Xu, Zhang Zhang

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引用次数: 0

Abstract

Motivation: Editome Disease Knowledgebase (EDK) is a curated resource of knowledge between RNA editome and human diseases. Since its first release in 2018, a number of studies have discovered previously uncharacterized editome-disease associations and generated an abundance of RNA editing datasets. Thus, it is desirable to make significant updates for EDK by incorporating more editome-disease associations as well as their related editing profiles.

Results: Here, we present EDK v2.0, an updated version of editome-disease associations based on both literature curation and integrative analysis. EDK v2.0 incorporates a curated collection of 1097 editome-disease associations involving 115 diseases from 321 publications. Meanwhile, based on a standardized pipeline, EDK v2.0 provides RNA editing profiles from 48 datasets covering 2536 samples across 55 diseases. Through differential analysis on RNA editing, it further identifies a total of 7190 differential edited genes and 86 242 differential editing sites (DESs), leading to 266 339 DES-disease associations. Moreover, a curated list of 28 160 cis-RNA editing QTL associations, 458 187 DES-RNA binding protein associations, and 21 DES-RNA secondary structure associations are annotated and added to EDK v2.0. Additionally, it is equipped with a series of user-friendly tools to facilitate RNA editing online analysis.

Availability and implementation: https://ngdc.cncb.ac.cn/edk/.

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来源期刊

Bioinformatics advances

CiteScore

1.60

自引率

0.00%

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