GAGE: Generally applicable gene set enrichment for pathway analysis

BMC Bioinformatics

Volumn 10, Issue , 2009, Pages

  Luo, Weijun ^a,b   Friedman, Michael S ^c   Shedden, Kerby ^a   Hankenson, Kurt D ^d   Woolf, Peter J ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

^b Howard Hughes Medical Institute Cold Spring Harbor Laboratory Cold Spring Harbor   (United States)

^c Thermogenesis Corp   (United States)

^d UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GENE EXPRESSION DATA ANALYSIS; GENE EXPRESSION DATASETS; MECHANISTIC SCHEME; MICROARRAY DATA SETS; OSTEOBLAST DIFFERENTIATION; REGULATORY MECHANISM; REGULATORY PATHWAY; SENSITIVITY AND SPECIFICITY;

BIOLOGICAL ORGANS; DISEASES; GENE EXPRESSION; STATISTICS;

GAGES;

BONE MORPHOGENETIC PROTEIN; BONE MORPHOGENETIC PROTEIN 6; ESTROGEN; JANUS KINASE; STAT PROTEIN; TRANSFORMING GROWTH FACTOR BETA; WNT PROTEIN; BMP6 PROTEIN, HUMAN;

ARTICLE; BIOINFORMATICS; CANCER GROWTH; CELL DIFFERENTIATION; COMPUTER PROGRAM; CONTROLLED STUDY; GENE EXPRESSION PROFILING; GENERALLY APPLICABLE GENE SET ENRICHMENT; GENETIC ANALYSIS; HUMAN; HUMAN CELL; INTERMETHOD COMPARISON; LUNG CANCER; MESENCHYMAL STEM CELL; METASTASIS; MICROARRAY ANALYSIS; OSTEOBLAST; REGULATORY MECHANISM; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; SIGNAL TRANSDUCTION; ALGORITHM; COMPUTER SIMULATION; DNA MICROARRAY; GENE REGULATORY NETWORK; GENETICS; LUNG TUMOR; METABOLISM; METHODOLOGY; REPRODUCIBILITY; STATISTICAL MODEL;

ALGORITHMS; BONE MORPHOGENETIC PROTEIN 6; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; HUMANS; LUNG NEOPLASMS; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL TRANSDUCTION; SOFTWARE;

EID: 67649202800     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-10-161     Document Type: Article

References (53)

1. Luo W Hankenson KD Woolf PJ Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual information BMC Bioinformatics 2008, 9:467. 2613931 18980677 10.1186/1471-2105-9-467
2. Nam D Kim SY Gene-set approach for expression pattern analysis Brief Bioinform 2008, 9:189-97. 10.1093/bib/bbn001 18202032
3. Subramanian A Tamayo P Mootha VK Mukherjee S Ebert BL Gillette MA Paulovich A Pomeroy SL Golub TR Lander ES Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles Proc Natl Acad Sci USA 2005, 102:15545-50. 1239896 16199517 10.1073/pnas.0506580102
4. Mootha VK Lindgren CM Eriksson KF Subramanian A Sihag S Lehar J Puigserver P Carlsson E Ridderstrale M Laurila E PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes Nat Genet 2003, 34:267-73. 10.1038/ ng1180 12808457
5. Kim SY Volsky DJ PAGE: Parametric analysis of gene set enrichment BMC Bioinformatics 2005, 6:144. 1183189 15941488 10.1186/1471-2105-6-144
6. Newton MA Quintana FA Den Boon JA Sengupta S Ahlquist P Random-set methods identify distinct aspects of the enrichment signal in gene-set analysis Ann Appl Stat 2007, 1:85-106. 10.1214/07-AOAS104
7. Boorsma A Foat BC Vis D Klis F Bussemaker HJ T-profiler: Scoring the activity of predefined groups of genes using gene expression data Nucleic Acids Res 2005, 33:W592-5. 1160244 15980543 10.1093/nar/gki484
8. 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, 102:13544-9. 1200092 16174746 10.1073/ pnas.0506577102
9. 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
10. Barry WT Nobel AB Wright FA Significance analysis of functional categories in gene expression studies: A structured permutation approach Bioinformatics 2005, 21:1943-9. 10.1093/bioinformatics/bti260 15647293
11. Goeman JJ Buhlmann P Analyzing gene expression data in terms of gene sets: Methodological issues Bioinformatics 2007, 23:980-7. 10.1093/ bioinformatics/btm051 17303618
12. Liu Q Dinu I Adewale AJ Potter JD Yasui Y Comparative evaluation of gene-set analysis methods BMC Bioinformatics 2007, 8:431. 2238724 17988400 10.1186/1471-2105-8-431
13. Zhang B Kirov S Snoddy J WebGestalt: An integrated system for exploring gene sets in various biological contexts Nucleic Acids Res 2005, 33:W741-8. 1160236 15980575 10.1093/nar/gki475
14. Al-Shahrour F Arbiza L Dopazo H Huerta-Cepas J Minguez P Montaner D Dopazo J From genes to functional classes in the study of biological systems BMC Bioinformatics 2007, 8:114. 1853114 17407596 10.1186/ 1471-2105-8-114
15. Nam D Kim SY Gene-set approach for expression pattern analysis Brief Bioinform 2008. 18202032
16. Bussemaker HJ Ward LD Boorsma A Dissecting complex transcriptional responses using pathway-level scores based on prior information BMC Bioinformatics 2007, 8(Suppl 6):S6. 1995543 17903287 10.1186/ 1471-2105-8-S6-S6
17. Baur JA Pearson KJ Price NL Jamieson HA Lerin C Kalra A Prabhu VV Allard JS Lopez-Lluch G Lewis K Resveratrol improves health and survival of mice on a high-calorie diet Nature 2006, 444:337-42. 10.1038/nature05354 17086191
18. Smid M Dorssers LC GO-Mapper: Functional analysis of gene expression data using the expression level as a score to evaluate Gene Ontology terms Bioinformatics 2004, 20:2618-25. 10.1093/bioinformatics/bth293 15130934
19. Saxena V Orgill D Kohane I Absolute enrichment: Gene set enrichment analysis for homeostatic systems Nucleic Acids Res 2006, 34:e151. 1702493 17130162 10.1093/nar/gkl766
20. Kemp DM Nirmala NR Szustakowski JD Extending the pathway analysis framework with a test for transcriptional variance implicates novel pathway modulation during myogenic differentiation Bioinformatics 2007, 23:1356-62. 10.1093/bioinformatics/btm116 17392327
21. Beer DG Kardia SL Huang CC Giordano TJ Levin AM Misek DE Lin L Chen G Gharib TG Thomas DG Gene-expression profiles predict survival of patients with lung adenocarcinoma Nat Med 2002, 8:816-24. 12118244
22. Bhattacharjee A Richards WG Staunton J Li C Monti S Vasa P Ladd C Beheshti J Bueno R Gillette M Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses Proc Natl Acad Sci USA 2001, 98:13790-5. 61120 11707567 10.1073/ pnas.191502998
23. The Molecular Signature Database http://www.broad.mit.edu/gsea/msigdb/
24. Dorsam RT Gutkind JS G-protein-coupled receptors and cancer Nat Rev Cancer 2007, 7:79-94. 10.1038/nrc2069 17251915
25. Li S Huang S Peng SB Overexpression of G protein-coupled receptors in cancer cells: Involvement in tumor progression Int J Oncol 2005, 27:1329-39. 16211229
26. Altiay G Ciftci A Demir M Kocak Z Sut N Tabakoglu E Hatipoglu ON Caglar T High plasma D-dimer level is associated with decreased survival in patients with lung cancer Clin Oncol (R Coll Radiol) 2007, 19:494-8. 17513096
27. Antoniou D Pavlakou G Stathopoulos GP Karydis I Chondrou E Papageorgiou C Dariotaki F Chaimala D Veslemes M Predictive value of D-dimer plasma levels in response and progressive disease in patients with lung cancer Lung Cancer 2006, 53:205-10. 10.1016/j.lungcan.2006.03.015 16769149
28. Montgrain PR Quintana R Rascon Y Burton DW Deftos LJ Casillas A Hastings RH Parathyroid hormone-related protein varies with sex and androgen status in nonsmall cell lung cancer Cancer 2007, 110:1313-20. 10.1002/ cncr.22922 17676588
29. Hidalgo GE Zhong L Doherty DE Hirschowitz EA Plasma PGE-2 levels and altered cytokine profiles in adherent peripheral blood mononuclear cells in non-small cell lung cancer (NSCLC) Mol Cancer 2002, 1:5. 149408 12459041 10.1186/1476-4598-1-5
30. Darnell JE Jr Kerr IM Stark GR Jak-STAT pathways and transcriptional activation in response to IFNs and other extracellular signaling proteins Science 1994, 264:1415-21. 10.1126/science.8197455 8197455
31. Kristof AS Marks-Konczalik J Billings E Moss J Stimulation of signal transducer and activator of transcription-1 (STAT1)-dependent gene transcription by lipopolysaccharide and interferon-gamma is regulated by mammalian target of rapamycin J Biol Chem 2003, 278:33637-44. 10.1074/ jbc.M301053200 12807916
32. Rajan P Panchision DM Newell LF McKay RD BMPs signal alternately through a SMAD or FRAP-STAT pathway to regulate fate choice in CNS stem cells J Cell Biol 2003, 161:911-21. 2172962 12796477 10.1083/jcb.200211021
33. Fujita K Janz S Attenuation of WNT signaling by DKK-1 and -2 regulates BMP2-induced osteoblast differentiation and expression of OPG, RANKL and M-CSF Mol Cancer 2007, 6:71. 2173906 17971207 10.1186/1476-4598-6-71
34. Rawadi G Vayssiere B Dunn F Baron R Roman-Roman S BMP-2 controls alkaline phosphatase expression and osteoblast mineralization by a Wnt autocrine loop J Bone Miner Res 2003, 18:1842-53. 10.1359/ jbmr.2003.18.10.1842 14584895
35. Kulterer B Friedl G Jandrositz A Sanchez-Cabo F Prokesch A Paar C Scheideler M Windhager R Preisegger KH Trajanoski Z Gene expression profiling of human mesenchymal stem cells derived from bone marrow during expansion and osteoblast differentiation BMC Genomics 2007, 8:70. 1829400 17352823 10.1186/1471-2164-8-70
36. Balint E Lapointe D Drissi H Meijden van der C Young DW van Wijnen AJ Stein JL Stein GS Lian JB Phenotype discovery by gene expression profiling: Mapping of biological processes linked to BMP-2-mediated osteoblast differentiation J Cell Biochem 2003, 89:401-26. 10.1002/ jcb.10515 12704803
37. Larsson J Karlsson S The role of Smad signaling in hematopoiesis Oncogene 2005, 24:5676-92. 10.1038/sj.onc.1208920 16123801
38. Maguer-Satta V Bartholin L Jeanpierre S Ffrench M Martel S Magaud JP Rimokh R Regulation of human erythropoiesis by activin A, BMP2, and BMP4, members of the TGFbeta family Exp Cell Res 2003, 282:110-20. 10.1016/S0014-4827(02)00013-7 12531697
39. Helms MW Packeisen J August C Schittek B Boecker W Brandt BH Buerger H First evidence supporting a potential role for the BMP/SMAD pathway in the progression of oestrogen receptor-positive breast cancer J Pathol 2005, 206:366-76. 10.1002/path.1785 15892165
40. Ong DB Colley SM Norman MR Kitazawa S Tobias JH Transcriptional regulation of a BMP-6 promoter by estrogen receptor alpha J Bone Miner Res 2004, 19:447-54. 10.1359/JBMR.0301249 15040833
41. Jiang Z Gentleman R Extensions to gene set enrichment Bioinformatics 2007, 23:306-13. 10.1093/bioinformatics/btl599 17127676
42. 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.
43. Shaffer JP Multiple Hypothesis-Testing Annu Rev Psychol 1995, 46:561-584. 10.1146/annurev.ps.46.020195.003021
44. Stonehouse JM Forrester GJ Robustness of the t and U tests under combined assumption violations Journal of Applied Statistics 1998, 25:63-74. 10.1080/02664769823304
45. Conover WJ Iman RL Rank Transformations as a Bridge between Parametric and Nonparametric Statistics American Statistician 1981, 35:124-129. 10.2307/2683975
46. Strimmer K A unified approach to false discovery rate estimation BMC Bioinformatics 2008, 9:303. 2475539 18613966 10.1186/1471-2105-9-303
47. GAGE R package http://sysbio.engin.umich.edu/~luow/downloads.php
48. Gene Annotation & Information Query (GAIQ) http://sysbio.engin.umich.edu/~luow/project/geneInfo.php
49. GSEA software http://www.broad.mit.edu/gsea/downloads.jsp
50. Furge KA Chen J Koeman J Swiatek P Dykema K Lucin K Kahnoski R Yang XJ Teh BT Detection of DNA copy number changes and oncogenic signaling abnormalities from gene expression data reveals MYC activation in high-grade papillary renal cell carcinoma Cancer Res 2007, 67:3171-6. 10.1158/0008-5472.CAN-06-4571 17409424
51. ChipperDB type 2 diabetes data set http://www.diabetesgenome.org/ chipperdb/expt.cgi?id=54
52. Gautier L Cope L Bolstad BM Irizarry RA affy-analysis of Affymetrix GeneChip data at the probe level Bioinformatics 2004, 20:307-15. 10.1093/ bioinformatics/btg405 14960456
53. Dai M Wang P Boyd AD Kostov G Athey B Jones EG Bunney WE Myers RM Speed TP Akil H Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data Nucleic Acids Res 2005, 33:e175. 1283542 16284200 10.1093/nar/gni179