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Toward comprehensive functional analysis of gene lists weighted by gene essentiality scores
Rui Fan1,2, Qinghua Cui1,2
1Department of Biomedical Informatics, MOE Key Lab of Cardiovascular Sciences, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
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.
