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CLIP-GENE: a web service of the condition specific context-laid integrative analysis for gene prioritization in mouse TF knockout experiments

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Authors
Hur, Benjamin; Lim, Sangsoo; Chae, Heejoon; Seo, Seokjun; Lee, Sunwon; Kang, Jaewoo; Kim, Sun
Issue Date
2016-10-24
Publisher
BioMed Central
Citation
Biology Direct, 11(1):57
Keywords
Knockout mouseGene prioritizationGene selectionWeb tool
Abstract
Motivation
Transcriptome data from the gene knockout experiment in mouse is widely used to investigate functions of genes and relationship to phenotypes. When a gene is knocked out, it is important to identify which genes are affected by the knockout gene. Existing methods, including differentially expressed gene (DEG) methods, can be used for the analysis. However, existing methods require cutoff values to select candidate genes, which can produce either too many false positives or false negatives. This hurdle can be addressed either by improving the accuracy of gene selection or by providing a method to rank candidate genes effectively, or both. Prioritization of candidate genes should consider the goals or context of the knockout experiment. As of now, there are no tools designed for both selecting and prioritizing genes from the mouse knockout data. Hence, the necessity of a new tool arises.

Results
In this study, we present CLIP-GENE, a web service that selects gene markers by utilizing differentially expressed genes, mouse transcription factor (TF) network, and single nucleotide variant information. Then, protein-protein interaction network and literature information are utilized to find genes that are relevant to the phenotypic differences. One of the novel features is to allow researchers to specify their contexts or hypotheses in a set of keywords to rank genes according to the contexts that the user specify. We believe that CLIP-GENE will be useful in characterizing functions of TFs in mouse experiments.

Availability
http://epigenomics.snu.ac.kr/CLIP-GENE

Reviewers
This article was reviewed by Dr. Lee and Dr. Pongor.
Language
English
URI
https://hdl.handle.net/10371/109873
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College of Natural Sciences (자연과학대학)Program in Bioinformatics (협동과정-생물정보학전공)Journal Papers (저널논문_협동과정-생물정보학전공)
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