iPEAP: integrating multiple omics and genetic data for pathway enrichment analysis

被引：25

作者：

Sun, Haoqi ^{[1
]}

Wang, Haiping ^{[2
]}

Zhu, Ruixin ^{[1
]}

Tang, Kailin ^{[1
]}

Gong, Qin ^{[1
]}

Cui, Juan ^{[3
]}

Cao, Zhiwei ^{[1
]}

Liu, Qi ^{[1
]}

机构：

[1] Tongji Univ, Sch Life Sci & Technol, Dept Bioinformat, Shanghai 200092, Peoples R China

[2] Hefei Univ Technol, Dept Comp Sci, Hefei 230009, Peoples R China

[3] Univ Georgia, Dept Biochem & Mol Biol, Athens, GA 30602 USA

来源：

BIOINFORMATICS | 2014年 / 30卷 / 05期

基金：

中国国家自然科学基金;

关键词：

RANK AGGREGATION; TRANSCRIPTOMICS;

D O I：

10.1093/bioinformatics/btt576

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

A challenge in biodata analysis is to understand the underlying phenomena among many interactions in signaling pathways. Such study is formulated as the pathway enrichment analysis, which identifies relevant pathways functional enriched in highthroughput data. The question faced here is how to analyze different data types in a unified and integrative way by characterizing pathways that these data simultaneously reveal. To this end, we developed integrative Pathway Enrichment Analysis Platform, iPEAP, which handles transcriptomics, proteomics, metabolomics and GWAS data under a unified aggregation schema. iPEAP emphasizes on the ability to aggregate various pathway enrichment results generated in different high-throughput experiments, as well as the quantitative measurements of different ranking results, thus providing the first benchmark platform for integration, comparison and evaluation of multiple types of data and enrichment methods.

引用

页码：737 / 739

页数：3

共 18 条

[1]

Chapelle O., 2009, CIKM 09 P 18 ACM C I, p[2, 621]

[2] Global functional profiling of gene expression [J].

Draghici, S ;

Khatri, P ;

Martins, RP ;

Ostermeier, GC ;

Krawetz, SA .

GENOMICS, 2003, 81 (02) :98-104

[3] A systems biology approach for pathway level analysis [J].

Draghici, Sorin ;

Khatri, Purvesh ;

Tarca, Adi Laurentiu ;

Amin, Kashyap ;

Done, Arina ;

Voichita, Calin ;

Georgescu, Constantin ;

Romero, Roberto .

GENOME RESEARCH, 2007, 17 (10) :1537-1545

[4] STRING v9.1: protein-protein interaction networks, with increased coverage and integration [J].

Franceschini, Andrea ;

Szklarczyk, Damian ;

Frankild, Sune ;

Kuhn, Michael ;

Simonovic, Milan ;

Roth, Alexander ;

Lin, Jianyi ;

Minguez, Pablo ;

Bork, Peer ;

von Mering, Christian ;

Jensen, Lars J. .

NUCLEIC ACIDS RESEARCH, 2013, 41 (D1) :D808-D815

[5] Differential Expression Analysis for Pathways [J].

Haynes, Winston A. ;

Higdon, Roger ;

Stanberry, Larissa ;

Collins, Dwayne ;

Kolker, Eugene .

PLOS COMPUTATIONAL BIOLOGY, 2013, 9 (03)

[6] Cumulated gain-based evaluation of IR techniques [J].

Järvelin, K ;

Kekäläinen, J .

ACM TRANSACTIONS ON INFORMATION SYSTEMS, 2002, 20 (04) :422-446

[7] Integrating transcriptomics and metabonomics to unravel modes-of-action of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in HepG2 cells [J].

Jennen, Danyel ;

Ruiz-Aracama, Ainhoa ;

Magkoufopoulou, Christina ;

Peijnenburg, Ad ;

Lommen, Arjen ;

van Delft, Joost ;

Kleinjans, Jos .

BMC SYSTEMS BIOLOGY, 2011, 5

[8] Integrative pathway analysis of genome-wide association studies and gene expression data in prostate cancer [J].

Jia, Peilin ;

Liu, Yang ;

Zhao, Zhongming .

BMC SYSTEMS BIOLOGY, 2012, 6

[9] Integrated pathway-level analysis of transcriptomics and metabolomics data with IMPaLA [J].

Kamburov, Atanas ;

Cavill, Rachel ;

Ebbels, Timothy M. D. ;

Herwig, Ralf ;

Keun, Hector C. .

BIOINFORMATICS, 2011, 27 (20) :2917-2918

[10] Robust rank aggregation for gene list integration and meta-analysis [J].

Kolde, Raivo ;

Laur, Sven ;

Adler, Priit ;

Vilo, Jaak .

BIOINFORMATICS, 2012, 28 (04) :573-580

← 1 2 →