Gene set enrichment analysis for non-monotone association and multiple experimental categories

BMC Bioinformatics

Volumn 9, Issue , 2008, Pages

  Lin, Rongheng ^a   Dai, Shuangshuang ^b   Irwin, Richard D ^a   Heinloth, Alexandra N ^a   Boorman, Gary A ^c   Li, Leping ^a  

^a NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES   (United States)

^b Alpha Gamma Technologies Inc   (United States)

^c UK   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION COEFFICIENT; FUNCTION AND EXPRESSION; GENE EXPRESSION LEVELS; GENE SET ENRICHMENT ANALYSIS; MICROARRAY DATA ANALYSIS; MULTIPLE CORRELATION COEFFICIENTS; SIGNIFICANCE ANALYSIS; STATISTICAL DEPENDENCIES;

AMINO ACIDS; BLOOD; STATISTICAL TESTS; STATISTICS;

GENE EXPRESSION;

PROTEOME;

ALGORITHM; ARTICLE; DNA MICROARRAY; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENETIC DATABASE; META ANALYSIS; METABOLISM; METHODOLOGY; PHENOTYPE; STATISTICS;

ALGORITHMS; DATABASES, GENETIC; GENE EXPRESSION; GENE EXPRESSION PROFILING; META-ANALYSIS AS TOPIC; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PHENOTYPE; PROTEOME;

EID: 60849088565     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-9-481     Document Type: Article

References (39)

1. Parmigiani G Garrett ES Irizarry RA Zeger SL (Eds) The Analysis of Gene Expression Data. Springer 2003
2. Smyth GK Yang YH Speed T Statistical issues in cDNA microarray data analysis Methods Mol Biol 2003, 224:111-136 12710670
3. Mootha VK Lindgren CM Eriksson KF Subramanian A Sihag S Lehar J Puigserver P Carlsson E Ridderstrale M Laurila E Houstis N Daly MJ Patterson N Mesirov JP Golub TR Tamayo P Spiegelman B Lander ES Hirschhorn JN Altshuler D Groop LC PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes Nat Genet 2003, 34(3):267-273 10.1038/ng1180 12808457
4. Subramanian A Tamayo P Mootha VK Mukherjee S Ebert BL Gillette MA Paulovich A Pomeroy SL Golub TR Lander ES Mesirov JP Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles Proc Natl Acad Sci USA 2005, 102(43):15545-15550 1239896 16199517 10.1073/pnas.0506580102
5. Barry WT Nobel AB Wright FA Significance analysis of functional categories in gene expression studies: A structured permutation approach Bioinformatics 2005, 21(9):1943-1949 10.1093/bioinformatics/bti260 15647293
6. Edelman E Porrello A Guinney J Balakumaran B Bild A Febbo PG Mukherjee S Analysis of sample set enrichment scores: Assaying the enrichment of sets of genes for individual samples in genome-wide expression profiles Bioinformatics 2006, 22(14):e108-e116 10.1093/bioinformatics/btl231 16873460
7. Tian L Greenberg SA Kong SW Altschuler J Kohane IS Park PJ Discovering statistically significant pathways in expression profiling studies Proc Natl Acad Sci USA 2005, 102(38):13544-13549 1200092 16174746 10.1073/ pnas.0506577102
8. Goeman JJ Bühlmann P Analyzing gene expression data in terms of gene sets: Methodological issues Bioinformatics 2007, 23(8):980-987 10.1093/bioinformatics/btm051 17303618
9. Chen JJ Lee T Delongchamp RR Chen T Tsai CA Significant Analysis of Groups of Genes in Expression Profiling Studies Bioinformatics 2007
10. Jiang Z Gentleman R Extensions to gene set enrichment Bioinformatics 2007, 23(3):306-313 10.1093/bioinformatics/btl599 17127676
11. Gold DL Coombes KR Wang J Mallick B Enrichment analysis in high-throughput genomics - accounting for dependency in the NULL Brief Bioinform 2007, 8(2):71-77 10.1093/bib/bbl019 17077137
12. Tusher VG Tibshirani R Chu G Significance analysis of microarrays applied to the ionizing radiation response Procedings of National Academy of Sciences 2001, 98(9):5116-5121 10.1073/pnas.091062498
13. Efron B Tibshirani R Storey JD Tusher V Empirical Bayes analysis of a microarray experiment Journal of the American Statistical Association 2001, 96(456):1151-1160 10.1198/016214501753382129
14. Lönnstedt I Speed T Replicated microarray data Statistica Sinica 2002, 12:31-46
15. Smyth GK Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments Statistical Applications in Genetics and Molecular Biology 2004 3 http://www.bepress.com/sagmb/vol3/iss1/art3
16. Cui X Hwang JTG Qiu J Blades NJ Churchill GA Improved statistical tests for differential gene expression by shrinking variance components estimates Biostatistics 2005, 6:59-75 10.1093/biostatistics/kxh018 15618528
17. Newton MA Noueiry A Sarkar D Ahlquist P Detecting differential gene expression with a semiparametric hierarchial mixture method Biostatistics 2004, 5(2):155-176 10.1093/biostatistics/5.2.155 15054023
18. Lin SM Johnson KF A practical approach to microarray data analysis Kluwer Academic Publishers 2003 chap. Correlation and Association Analysis 289-305
19. Irwin RD Boorman GA Cunningham ML Heinloth AN Malarkey DE Paules RS Application of toxicogenomics to toxicology: Basic concepts in the analysis of microarray data Toxicol Pathol 2004, 32(Suppl 1):72-83 10.1080/01926230490424752 15209406
20. De Boor C A practical guide to splines Springer, revised edition 2001
21. Doksum K Blyth S Bradlow E Meng XL Zhao H Correlation Curves As Local Measures of Variance Explained by Regression Journal of the American Statistical Association 1994, 89:571-582 10.2307/2290860
22. Hastie T Tibshirani R Generalized Additive Models Chapman & Hall Ltd 1999
23. R Development Core Team R: A language and environment for statistical computing R Foundation for Statistical Computing, Vienna, Austria 2005 http://www.R-project.org
24. Simonoff JS Smoothing Methods in Statistics Springer-Verlag Inc 1996
25. Frank IE Modern nonlinear regression methods Chemometrics and Intelligent Laboratory Systems 1995, 27:1-9 10.1016/0169-7439(94)00005-4
26. Goeman JJ Geer van de SA de Kort F van Houwelingen HC A global test for groups of genes: Testing association with a clinical outcome Bioinformatics 2004, 20:93-99 10.1093/bioinformatics/btg382 14693814
27. Dinu I Potter JD Mueller T Liu Q Adewale AJ Jhangri GS Einecke G Famulski KS Halloran P Yasui Y Improving gene set analysis of microarray data by SAM-GS BMC Bioinformatics 2007, 8:242 1931607 17612399 10.1186/ 1471-2105-8-242
28. Damian D Gorfine M Statistical concerns about the GSEA procedure Nature Genetics 2004, 36:663 10.1038/ng0704-663a 15226741
29. Mootha VK Daly MJ Patterson N Hirchhorn JN Groop LC Altshuler D In reply to Statistical concerns about the GSEA procedure Nature Genetics 2004, 36:663 10.1038/ng0704-663b 15226741
30. Fisher RA Question 14: Combining Independent Tests of Significance The American Statistician 1948, 2,5(5):30
31. Benjamini Y Hochberg Y Controlling the false discovery rate: A practical and powerful approach to multiple testing Journal of the Royal Statistical Society, Series B, Methodological 1995, 57:289-300
32. Storey JD Tibshirani R Statistical Significance for Genomewide Studies Proceedings of the National Academy of Science 2003, 100:9440-9445 10.1073/pnas.1530509100
33. Fan J Ren Y Statistical analysis of DNA microarray data in cancer research Clin Cancer Res 2006, 12(15):4469-4473 10.1158/ 1078-0432.CCR-06-1033 16899590
34. Bushel PR Heinloth AN Li J Huang L Chou JW Boorman GA Malarkey DE Houle CD Ward SM Wilson RE Fannin RD Russo MW Watkins PB Tennant RW Paules RS Blood gene expression signatures predict exposure levels Proc Natl Acad Sci USA 2007, 104(46):18211-18216 2084322 17984051 10.1073/ pnas.0706987104
35. Eisen MB Spellman PT Brown PO Botstein D Cluster analysis and display of genome-wide expression patterns Proc Natl Acad Sci USA 1998, 95(25):14863-14868 24541 9843981 10.1073/pnas.95.25.14863
36. Dudoit S Yang YH Callow MJ Speed TP Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments Statistica Sinica 2002, 12:111-139
37. Barry WT Significance Analysis of Function and Expression 2005
38. Gentleman RC Carey VJ Bates DM Bolstad B Dettling M Dudoit S Ellis B Gautier L Ge Y Gentry J Hornik K Hothorn T Huber W Iacus S Irizarry R Leisch F Li C Maechler M Rossini AJ Sawitzki G Smith C Smyth G Tierney L Yang JYH Zhang J Bioconductor: Open software development for computational biology and bioinformatics Genome Biol 2004, 5(10) 545600 15461798
39. Yekutieli D Benjamini Y Resampling-based False Discovery Rate Controlling Multiple Test Procedures for Correlated Test Statistics Journal of Statistical Planning and Inference 1999, 82:171-196 10.1016/ S0378-3758(99)00041-5