Integrative set enrichment testing for multiple omics platforms

BMC Bioinformatics

Volumn 12, Issue 1, 2011, Pages

  Poisson, Laila M ^a   Taylor, Jeremy M ^b   Ghosh, Debashis ^c  

^a HENRY FORD HOSPITAL   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

^c PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DIFFERENTIAL EXPRESSIONS; JOINT TEST; LOGISTIC REGRESSIONS; METABOLOMICS; MOLECULAR ASPECTS; MULTIPLE PLATFORMS; NOVEL METHODS; TYPE-I ERROR;

COMPUTER SIMULATION;

GENE EXPRESSION;

ARTICLE; COMPUTER SIMULATION; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENOMICS; HUMAN; METABOLOMICS; METHODOLOGY; PHENOTYPE; STATISTICAL MODEL;

COMPUTER SIMULATION; GENE EXPRESSION PROFILING; GENOMICS; HUMANS; LOGISTIC MODELS; METABOLOMICS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PHENOTYPE;

EID: 82055164075     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-12-459     Document Type: Article

References (15)

1. Sreekumar A, Poisson L, Rajendiran T, Khan A, Cao Q, Yu J, Laxman B, Mehra R, Lonigro R, Li Y, Nyati M, Ahsan A, Kalyana-Sundaram S, Han B, Cao X, Byun J, Omenn G, Ghosh D, Pennathur S, Alexander D, Berger A, Shuster J, Wei J, Varambally S, Beecher C, Chinnaiyan A. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature 2009, 457(7231):910-914. 10.1038/nature07762, 2724746, 19212411.
2. Weckwerth W. Integration of metabolomics and proteomics in molecular plant physiology and coping with the complexity by data-dimensionality reduction. Physiologia Plantarum 2008, 132:176-189. 10.1111/j.1399-3054.2007.01011.x, 18251859.
3. Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Research 2000, 28:27-30. 10.1093/nar/28.1.27, 102409, 10592173.
4. Network TCGAR Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 2008, 255:1061-1068. Network TCGAR.
5. Jones S, Zhang X, Parsons DW, Lin JC, Leary RJ, Angenendt P, Mankoo P, Carter H, Kamiyama H, Jimeno A, Hong SM, Fu B, Lin MT, Calhoun ES, Kamiyama M, Walter K, Nikolskaya T, Nikolsky Y, Hartigan J, Smith DR, Hidalgo M, Leach SD, Klein AP, Jaffee EM, Goggins M, Maitra A, Iacobuzio-Donahue C, Eshleman JR, Kern SE, Hruban RH, Karchin R, Papadopoulos N, Parmigiani G, Vogelstein B, Velculescu VE, Kinzler KW. Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science 2008, 321:1801-1806. 10.1126/science.1164368, 2848990, 18772397.
6. Goeman J, Bühlmann P. Analyzing gene expression data in terms of gene sets: methodological issues. Bioinformatics 2007, 23(8):980-987. 10.1093/bioinformatics/btm051, 17303618.
7. Nam D, Kim SY. Gene-set approach for expression pattern analysis. Briefings in Bioinformatics 2008, 9:189-197. 10.1093/bib/bbn001, 18202032.
8. Allison DB, Cui X, Page GP, Sabripour M. Gene-set approach for expression pattern analysis. Nature Reviews Genetics 2006, 7:55-65. 10.1038/nrg1749, 16369572.
9. Sartor MA, Leikauf GD, Medvedovic M. LRpath: a logistic regression approach for identifying enriched biological groups in gene expression data. Bioinformatics 2009, 25:211-217. 10.1093/bioinformatics/btn592, 2639007, 19038984.
10. Ackermann M, Strimmer K. A general modular framework for gene set enrichment analysis. BMC Bioinformatics 2009, 10:47. 10.1186/1471-2105-10-47, 2661051, 19192285.
11. Spicker JS, Brunak S, Frederiksen KS, Toft H. Integration of clinical chemistry, expression, and metabolite data leads to better toxicological class separation. Toxicol Sci 2008, 102:444-454.
12. Fisher RA. Questions and answers #14. The American Statistician 1948, 2:30-31.
13. De Maesschalck R, Jouan-Rimbaud D, Massart DL. The Mahalanobis distance. Chemometrics and Intelligent Laboratory Systems 2000, 50:1-18.
14. Carrari F, Baxter C, Usadel B, Urbanczyk-Wochniak E, Zanor MI, Nunes-Nesi A, Nikiforova V, Centero D, Ratzka A, Pauly M, Sweetlove LJ, Fernie AR. Integrated analysis of metabolite and transcript levels reveals the metabolic shifts that underlie tomato fruit development and highlight regulatory aspects of metabolic network behavior. Plant Physiol 2006, 142:1380-1396. 10.1104/pp.106.088534, 1676044, 17071647.
15. Kost J, McDermott M. Combining dependent P-values. Statistics and Probability Letters 2002, 60:183-190.