Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions

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• 作者：Patrick Y.P. Kao^a ; Kim Hung Leung^b ; Lawrence W.C. Chan^b ; Shea Ping Yip^b ; ^{shea.ping.yip@polyu.edu.hk} ; Maurice K.H. Yap^a
• 关键词：ARTP ; adaptive rank truncated product ; BMI ; body mass index ; (r)BEE ; (robust) brain-expressed enhancer ; CNV ; copy number variation ; eQTL ; expression quantitative trait locus ; ESI-MS/MS ; electrospray ionization mass spectrometry ; eSNP ; expression single-nucleotide polymorphism ; GCN ; gene coexpression network ; G-E ; gene-environment ; G-G ; gene-gene ; GEWIS ; genome-wide interaction study ; GO ; gene ontology ; GRN ; gene regulatory network ; GSAA ; gene set association analysis ; GSEA ; gene set enrichment a
• 刊名：Biochimica et Biophysica Acta (BBA) - General Subjects
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：1861
• 期：2
• 页码：335-353
• 全文大小：1320 K
• 卷排序：1861

文摘

Pathway analysis (PA) combines variant effects in genome-wide association studies. Many factors are considered when choosing appropriate software for PA. PA can also be used for other data: rare variants, other -omics & interaction data. PA can be expanded to other data types to improve disease outcome prediction.