基因命名
基因
集合(抽象数据类型)
基因注释
计算生物学
计算机科学
基因预测
生物
遗传学
基因组
程序设计语言
分类学(生物学)
植物
命名法
出处
期刊:Bioinformatics
[Oxford University Press]
日期:2021-06-25
卷期号:37 (23): 4399-4404
被引量:8
标识
DOI:10.1093/bioinformatics/btab475
摘要
Abstract Motivation Gene functional enrichment analysis represents one of the most popular bioinformatics methods for annotating the pathways and function categories of a given gene list. Current algorithms for enrichment computation such as Fisher’s exact test and hypergeometric test totally depend on the category count numbers of the gene list and one gene set. In this case, whatever the genes are, they were treated equally. However, actually genes show different scores in their essentiality in a gene list and in a gene set. It is thus hypothesized that the essentiality scores could be important and should be considered in gene functional analysis. Results For this purpose, here, we proposed weighted enrichment analysis tool (WEAT) (https://www.cuilab.cn/weat/), a weighted gene set enrichment algorithm and online tool by weighting genes using essentiality scores. We confirmed the usefulness of WEAT using three case studies, the functional analysis of one aging-related gene list, one gene list involved in Lung Squamous Cell Carcinoma and one cardiomyopathy gene list from Drosophila model. Finally, we believe that the WEAT method and tool could provide more possibilities for further exploring the functions of given gene lists. Availability and implementation The datasets generated and analyzed during the current study are available on our website at https://www.cuilab.cn/weat/. Supplementary information Supplementary data are available at Bioinformatics online.
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