Analyzing Illumina Gene Expression Microarray Data from Different Tissues: Methodological Aspects of Data Analysis in the MetaXpress Consortium

PLoS ONE

Volumn 7, Issue 12, 2012, Pages

  Schurmann, Claudia ^a   Heim, Katharina ^b   Schillert, Arne ^c,e   Blankenberg, Stefan ^d,e   Carstensen, Maren ^f   Dörr, Marcus ^e,g   Endlich, Karlhans ^g   Felix, Stephan B ^e,g   Gieger, Christian ^b   Grallert, Harald ^b   Herder, Christian ^f   Hoffmann, Wolfgang ^e,g   Homuth, Georg ^a   Illig, Thomas ^b,h   Kruppa, Jochen ^c,e   Meitinger, Thomas ^b,e,i,j   Müller, Christian ^d   Nauck, Matthias ^e,g   Peters, Annette ^b,e,j   Rettig, Rainer ^g   Roden, Michael ^f,k   Strauch, Konstantin ^b,l   Völker, Uwe ^a,e   Völzke, Henry ^e,g   Wahl, Simone ^b   Wallaschofski, Henri ^e,g   Wild, Philipp S ^e,m   Zeller, Tanja ^d,e   Teumer, Alexander ^a   Prokisch, Holger ^b,e,i   Ziegler, Andreas ^c,e   more..

^a UNIVERSITY OF GREIFSWALD   (Germany)

^b INSTITUTE OF EPIDEMIOLOGY   (Germany)

^c UNIVERSITY HOSPITAL SCHLESWIG HOLSTEIN   (Germany)

^d UNIVERSITY HEART CENTER HAMBURG   (Germany)

^e DZHK GERMAN CENTRE FOR CARDIOVASCULAR RESEARCH   (Germany)

^f HEINRICH HEINE UNIVERSITY   (Germany)

^g UNIVERSITY MEDICINE GREIFSWALD   (Germany)

^h HANNOVER MEDICAL SCHOOL   (Germany)

ⁱ TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^j Munich Heart Alliance   (Germany)

^k UNIVERSITY HOSPITAL DÜSSELDORF   (Germany)

^l UNIVERSITY OF MUNICH   (Germany)

^m UNIVERSITY MEDICAL CENTER MAINZ   (Germany)

more..

Author keywords

[No Author keywords available]

Indexed keywords

MESSENGER RNA;

ADULT; AGED; ARTICLE; BLOOD CELL; BLOOD DONOR; CELL COMPOSITION; COHORT ANALYSIS; CONTROLLED STUDY; DATA PROCESSING; FEMALE; GENE AMPLIFICATION; GENE EXPRESSION; GENE FREQUENCY; HUMAN; HUMAN CELL; HUMAN TISSUE; HYBRIDIZATION; MALE; MICROARRAY ANALYSIS; MOLECULAR PROBE; MONOCYTE; POPULATION RESEARCH; PRINCIPAL COMPONENT ANALYSIS; RNA ANALYSIS; RNA ISOLATION; SIGNAL DETECTION; SINGLE NUCLEOTIDE POLYMORPHISM;

GENE EXPRESSION; GENE EXPRESSION PROFILING; GERMANY; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; POLYMORPHISM, SINGLE NUCLEOTIDE; REPRODUCIBILITY OF RESULTS;

EID: 84870895128     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0050938     Document Type: Article

References (45)

1. Ramasamy A, Mondry A, Holmes CC, Altman DG, (2008) Key issues in conducting a meta-analysis of gene expression microarray datasets. PLoS Med 5: e184.
2. Heinig M, Petretto E, Wallace C, Bottolo L, Rotival M, et al. (2010) A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk. Nature 467: 460-464.
3. Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, et al. (2003) Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci U S A 100: 10393-10398.
4. van de Vijver MJ, He YD, van't Veer LJ, Dai H, Hart AAM, et al. (2002) A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347: 1999-2009.
5. van 't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AAM, et al. (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415: 530-536.
6. Staunton JE, Slonim DK, Coller HA, Tamayo P, Angelo MJ, et al. (2001) Chemosensitivity prediction by transcriptional profiling. Proc Natl Acad Sci U S A 98: 10787-10792.
7. Robert J, Vekris A, Pourquier P, Bonnet J, (2004) Predicting drug response based on gene expression. Crit Rev Oncol Hematol 51: 205-227.
8. Starling RC, Pham M, Valantine H, Miller L, Eisen H, et al. (2006) Molecular testing in the management of cardiac transplant recipients: initial clinical experience. J Heart Lung Transplant 25: 1389-1395.
9. Paik S, Tang G, Shak S, Kim C, Baker J, et al. (2006) Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol 24: 3726-3734.
10. Ein-Dor L, Kela I, Getz G, Givol D, Domany E, (2005) Outcome signature genes in breast cancer: is there a unique set? Bioinformatics 21: 171-178.
11. Ntzani EE, Ioannidis JPA, (2003) Predictive ability of dna microarrays for cancer outcomes and correlates: an empirical assessment. Lancet 362: 1439-1444.
12. Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, et al. (2001) Minimum information about a microarray experiment (miame)-toward standards for microarray data. Nat Genet 29: 365-371.
13. Brannon AR, Haake SM, Hacker KE, Pruthi RS, Wallen EM, et al. (2012) Meta-analysis of clear cell renal cell carcinoma gene expression defines a variant subgroup and identifies gender influences on tumor biology. Eur Urol 61: 258-268.
14. Fekete T, Rásó E, Pete I, Tegze B, Liko I, et al. (2012) Meta-analysis of gene expression profiles associated with histological classification and survival in 829 ovarian cancer samples. Int J Cancer 131: 95-105.
15. Miller BG, Stamatoyannopoulos JA, (2010) Integrative meta-analysis of differential gene expression in acute myeloid leukemia. PLoS One 5: e9466.
16. Györffy B, Schäfer R, (2009) Meta-analysis of gene expression profiles related to relapse-free survival in 1,079 breast cancer patients. Breast Cancer Res Treat 118: 433-441.
17. Roder C, Kasuya H, Harati A, Tatagiba M, Inoue I, et al. (2012) Meta-analysis of microarray gene expression studies on intracranial aneurysms. Neuroscience 201: 105-113.
18. Arasappan D, Tong W, Mummaneni P, Fang H, Amur S, (2011) Meta-analysis of microarray data using a pathway-based approach identifies a 37-gene expression signature for systemic lupus erythematosus in human peripheral blood mononuclear cells. BMC Med 9: 65.
19. Martini P, Risso D, Sales G, Romualdi C, Lanfranchi G, et al. (2011) Statistical test of expression pattern (stepath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies. BMC Bioinformatics 12: 92.
20. Choi H, Shen R, Chinnaiyan AM, Ghosh D, (2007) A latent variable approach for meta-analysis of gene expression data from multiple microarray experiments. BMC Bioinformatics 8: 364.
21. Rhodes DR, Kalyana-Sundaram S, Mahavisno V, Varambally R, Yu J, et al. (2007) Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia 9: 166-180.
22. Ochsner SA, Steffen DL, Hilsenbeck SG, Chen ES, Watkins C, et al. (2009) Gems (gene expression metasignatures), a web resource for querying meta-analysis of expression microarray datasets: 17beta-estradiol in mcf-7 cells. Cancer Res 69: 23-26.
23. Hruz T, Laule O, Szabo G, Wessendorp F, Bleuler S, et al. (2008) Genevestigator v3: a reference expression database for the meta-analysis of transcriptomes. Adv Bioinformatics 2008: 420747.
24. Hong F, Breitling R, McEntee CW, Wittner BS, Nemhauser JL, et al. (2006) Rankprod: a bioconductor package for detecting differentially expressed genes in meta-analysis. Bioinformatics 22: 2825-2827.
25. Eysenck HJ, (1994) Meta-analysis and its problems. BMJ 309: 789-792.
26. Campain A, Yang YH, (2010) Comparison study of microarray meta-analysis methods. BMC Bioinformatics 11: 408.
27. Repsilber D, Fink L, Jacobsen M, Bläsing O, Ziegler A, (2005) Sample selection for microarray gene expression studies. Methods Inf Med 44: 461-467.
28. Völzke H, Alte D, Schmidt CO, Radke D, Lorbeer R, et al. (2011) Cohort profile: The study of health in pomerania. Int J Epidemiol 40: 294-307.
29. Holle R, Happich M, Löwel H, Wichmann HE, (2005) MONICA/KORAStudyGroup (2005) Kora-a research platform for population based health research. Gesundheitswesen 67(Suppl 1):: S19-S25.
30. Zeller T, Wild P, Szymczak S, Rotival M, Schillert A, et al. (2010) Genetics and beyond-the transcriptome of human monocytes and disease susceptibility. PLoS One 5: e10693.
31. Du P, Kibbe WA, Lin SM, (2008) lumi: a pipeline for processing illumina microarray. Bioinformatics 24: 1547-1548.
32. Lin SM, Du P, Huber W, Kibbe WA, (2008) Model-based variance-stabilizing transformation for illumina microarray data. Nucleic Acids Res 36: e11.
33. Fehrmann RSN, Jansen RC, Veldink JH, Westra HJ, Arends D, et al. (2011) Trans-eqtls reveal that independent genetic variants associated with a complex phenotype converge on intermediate genes, with a major role for the hla. PLoS Genet 7: e1002197.
34. Xu Q, Ni S, Wu F, Liu F, Ye X, et al. (2011) Investigation of variation in gene expression profiling of human blood by extended principle component analysis. PLoS One 6: e26905.
35. Chen LS, Storey JD, (2008) Eigen-r2 for dissecting variation in high-dimensional studies. Bioinformatics 24: 2260-2262.
36. Kent WJ, Sugnet CW, Furey TS, Roskin KM, Pringle TH, et al. (2002) The human genome browser at ucsc. Genome Res 12: 996-1006.
37. Dreszer TR, Karolchik D, Zweig AS, Hinrichs AS, Raney BJ, et al. (2012) The ucsc genome browser database: extensions and updates 2011. Nucleic Acids Res 40: D918-D923.
38. Schmid R, Baum P, Ittrich C, Fundel-Clemens K, Huber W, et al. (2010) Comparison of normalization methods for illumina beadchip humanht-12 v3. BMC Genomics 11: 349.
39. Fu J, Wolfs MGM, Deelen P, Westra HJ, Fehrmann RSN, et al. (2012) Unraveling the regulatory mechanisms underlying tissue-dependent genetic variation of gene expression. PLoS Genet 8: e1002431.
40. Landi D, Gemignani F, Naccarati A, Pardini B, Vodicka P, et al. (2008) Polymorphisms within micro-rna-binding sites and risk of sporadic colorectal cancer. Carcinogenesis 29: 579-584.
41. Wild PS, Sinning CR, Roth A, Wilde S, Schnabel RB, et al. (2010) Distribution and categorization of left ventricular measurements in the general population: results from the population-based gutenberg heart study. Circ Cardiovasc Imaging 3: 604-613.
42. Rathmann W, Strassburger K, Heier M, Holle R, Thorand B, et al. (2009) Incidence of type 2 diabetes in the elderly german population and the effect of clinical and lifestyle risk factors: Kora s4/f4 cohort study. Diabet Med 26: 1212-1219.
43. Allen JD, Wang S, Chen M, Girard L, Minna JD, et al. (2011) Probe mapping across multiple microarray platforms. Brief Bioinform.
44. Barbosa-Morais NL, Dunning MJ, Samarajiwa SA, Darot JFJ, Ritchie ME, et al. (2010) A re-annotation pipeline for illumina beadarrays: improving the interpretation of gene expression data. Nucleic Acids Res 38: e17.
45. R Development Core Team (2006) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org. ISBN 3-900051-07-0.