title: CPAS: a trans-omics pathway analysis tool for jointly analyzing DNA copy number variations and mRNA expression profiles data.
abstract: Pathway-based analysis approaches provide additional insights into the pathogenesis of complex diseases. Copy number variations (CNVs) play an important role in gene expression regulation. Joint pathway analysis of CNVs and gene expression data should provide more useful information for revealing the molecular mechanism of complex diseases. To implement trans-omics pathway analysis of genome-wide CNVs and mRNA expression profiles data, we extended the gene set enrichment analysis algorithm and developed a flexible trans-omics pathway analysis tool CPAS. CPAS was developed by C to interface with R for efficient data analysis. CNV-gene and pathway-gene annotation files derived from public database were included in CPAS. We hope that CPAS could help to identify disease-relevant biological pathways that were undetectable using traditional single-omic analysis approaches.
authors.affiliation: Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China. Electronic address: fzhxjtu@mail.xjtu.edu.cn.
authors.forename: Feng
authors.initials: F
authors.lastname: Zhang
authors.affiliation: Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China.
authors.forename: Xiao
authors.initials: X
authors.lastname: Xiao
authors.affiliation: Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China.
authors.forename: Jingcan
authors.initials: J
authors.lastname: Hao
authors.affiliation: Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China.
authors.forename: Sen
authors.initials: S
authors.lastname: Wang
authors.affiliation: Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Wen
authors.affiliation: Key Laboratory of Trace Elements and Endemic Diseases of National Health and Family Planning Commission, School of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, PR China. Electronic address: guox@mail.xjtu.edu.cn.
authors.forename: Xiong
authors.initials: X
authors.lastname: Guo
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D056915:DNA Copy Number Variations; D015870:Gene Expression; D020869:Gene Expression Profiling; D016678:Genome; D006801:Humans; D057767:Kashin-Beck Disease / Q000175:diagnosis / Q000235:genetics*; D058977:Molecular Sequence Annotation; D020641:Polymorphism, Single Nucleotide; D012333:RNA, Messenger / Q000378:metabolism; D012984:Software
chemical_list: D012333:RNA, Messenger
keywords: CPAS; Copy number variations; Gene expression; Pathway analysis