A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer.

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作者： Mary Qu,Yang ^[1] ; Dan,Li ^[2] ; William,Yang ^[1] ; Yifan,Zhang ^[2] ; Jun,Liu ^[3] ; Weida,Tong ^[1]

作者单位： Joint Bioinformatics Graduate Program, Department of Information Science, George W. Donaghey College of Engineering and Information Technology, University of Arkansas at Little Rock, USA. ^[1] University of Arkansas for Medical Sciences, 2801 S. University Ave, Little Rock, AR 72204, USA. ^[2] School of Computer Science, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213, USA. ^[3] Department of Statistics, Harvard University, Cambridge, MA 02138, USA. ^[4] Divisions of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, 3900 NCTR Road, Jefferson, AR 72079, USA. ^[5]

关键词 AUC, Area Under Curve Causative mutation DEG, Differentially expressed gene DGM, Differential gene module Gene module KEGG, Kyoto Encyclopedia of Genes and Genomes Pathways Protein-protein interaction RCC, Renal cell cancer ROC, Receiver Operating Characteristic SVM, Support vector machine TCGA, The Cancer Genome Atlas ccRCC ccRCC, Clear cell renal cell carcinoma eQTL eQTL, Expression quantitative trait loci

DOI 10.1016/j.csbj.2017.09.003

PMID 29158875

发布时间 2023-08-10

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Computational and structural biotechnology journal

2017年15卷

463-470页

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A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer.

Computational and structural biotechnology journal

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A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer.

Computational and structural biotechnology journal

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Computational and structural biotechnology journal

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