Comparison of multiplex meta analysis techniques for understanding the acute rejection of solid organ transplants

BMC Bioinformatics

Volumn 11, Issue SUPPL. 9, 2010, Pages

  Morgan, Alexander A ^a   Khatri, Purvesh ^a,b   Jones, Richard H ^a   Sarwal, Minnie M ^a,b   Butte, Atul J ^a,b  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b LUCILE PACKARD CHILDREN S HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL SIGNALS; IMMUNE RESPONSE; MULTIPLEX ANALYSIS; NONPARAMETRIC METHODS; ORGAN TRANSPLANTS; PARAMETRIC EFFECTS; PARAMETRIC METHOD; TRANSPLANT REJECTION;

GENE EXPRESSION; TRANSPLANTATION (SURGICAL);

MULTIPLEXING;

ARTICLE; COMPARATIVE STUDY; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENETICS; GRAFT REJECTION; META ANALYSIS (TOPIC); METABOLISM; METHODOLOGY; ORGAN TRANSPLANTATION;

GENE EXPRESSION; GENE EXPRESSION PROFILING; GRAFT REJECTION; META-ANALYSIS AS TOPIC; ORGAN TRANSPLANTATION;

EID: 78049483770     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-S9-S6     Document Type: Article

References (27)

1. Choi JK, Yu U, Kim S, Yoo OJ. Combining multiple microarray studies and modeling interstudy variation. Bioinformatics 2003, 19(Suppl 1):i84-90. 10.1093/bioinformatics/btg1010, 12855442.
2. DeConde RP, Hawley S, Falton S, Clegg N, Knudsen B, Etzioni R. "Combining Results of Microarray Experiments: Rank Aggregation Approach". Statistical Applications in Genetics and Molecular Biology 2006, 5(1). 10.2202/1544-6115.1204, 17049026.
3. English SB, Butte AJ. Evaluation and integration of 49 genome-wide experiments and the prediction of previously unknown obesity-related genes. Bioinformatics 2007, 23(21):2910-2917. 10.1093/bioinformatics/btm483, 2839901, 17921495.
4. Ramasamy A, Mondry A, Holmes CC, Altman DG. Key issues in conducting a meta-analysis of gene expression microarray datasets. PLoS Med 2008, 5(9):e184. 10.1371/journal.pmed.0050184, 2528050, 18767902.
5. Rhodes DR, Barrette TR, Rubin MA, Ghost D, Chinnaaiyan AM. Meta-Analysis of Microarrays: Interstudy Validation of Gene Expression Profiles Reveals Pathway Dysregulation in Prostate Cancer. Cancer Res 2002, 62:4427-4433.
6. Hong F, Breitling R. A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments. Bioinformatics 2008, 24(3):374-382. 10.1093/bioinformatics/btm620, 18204063.
7. Number of U.S. Transplants Per Year, 1988-2008. , http://www.infoplease.com/science/health/us-transplants-year-1988-2007.html
8. Hedges L, Olkin I. Statistical methods for meta-analysis. 1985,
9. Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci U S A 2003, 100(16):9440-9445. 10.1073/pnas.1530509100, 170937, 12883005.
10. 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 1985, 57:289-300.
11. Witten D, Tibshirani R. A comparison of fold-change and the t-statistic for microarray data analysis. 2007, Stanford University.
12. Shi L, al E. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat Biotechnol 2006, 24(9):1151-1161. 10.1038/nbt1239, 16964229.
13. Cui X, Churchill G. Statistical tests for differential expression in cDNA microarray experiments. Genome biology 2003, 4(4):210. 10.1186/gb-2003-4-4-210, 154570, 12702200.
14. Cui X, Churchill GA. Statistical tests for differential expression in cDNA microarray experiments. Genome Biol 2003, 4(4):210. 10.1186/gb-2003-4-4-210, 154570, 12702200.
15. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 2005, 102(43):15545-15550. 10.1073/pnas.0506580102, 1239896, 16199517.
16. Rodder S, Scherer A, Raulf F, Berthier CC, Hertig A, Couzi L, Durrbach A, Rondeau E, Marti HP. Renal allografts with IF/TA display distinct expression profiles of metzincins and related genes. Am J Transplant 2009, 9(3):517-526. 10.1111/j.1600-6143.2008.02512.x, 19191772.
17. Flechner SM, Kurian SM, Head SR, Sharp SM, Whisenant TC, Zhang J, Chismar JD, Horvath S, Mondala T, Gilmartin T, et al. Kidney transplant rejection and tissue injury by gene profiling of biopsies and peripheral blood lymphocytes. Am J Transplant 2004, 4(9):1475-1489. 10.1111/j.1600-6143.2004.00526.x, 2041877, 15307835.
18. Gimino VJ, Lande JD, Berryman TR, King RA, Hertz MI. Gene expression profiling of bronchoalveolar lavage cells in acute lung rejection. Am J Respir Crit Care Med 2003, 168(10):1237-1242. 10.1164/rccm.200305-644OC, 12958056.
19. Patil J, Lande JD, Li N, Berryman TR, King RA, Hertz MI. Bronchoalveolar lavage cell gene expression in acute lung rejection: development of a diagnostic classifier. Transplantation 2008, 85(2):224-231. 10.1097/TP.0b013e318160268a, 18212627.
20. Karason K, Jernas M, Hagg DA, Svensson PA. Evaluation of CXCL9 and CXCL10 as circulating biomarkers of human cardiac allograft rejection. BMC Cardiovasc Disord 2006, 6:29. 10.1186/1471-2261-6-29, 1569871, 16780603.
21. Barrett T, Troup DB, Wilhite SE, Ledoux P, Rudnev D, Evangelista C, Kim IF, Soboleva A, Tomashevsky M, Edgar R. NCBI GEO: mining tens of millions of expression profiles--database and tools update. Nucleic Acids Res 2007, 35(Database issue):D760-765. 10.1093/nar/gkl887, 1669752, 17099226.
22. Gentleman R, Carey VJ, Huber W, Irizarry RA, Dudoit S. Bioinformatics and Computational Biology Solutions Using R and Bioconductor. 2005, New York: Springer-Verlag.
23. Wheeler DL, Barrett T, Benson DA, Bryant SH, Canese K, Chetvernin V, Church DM, DiCuccio M, Edgar R, Federhen S, et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res 2007, 35(Database issue):D5-12. 10.1093/nar/gkl1031, 1781113, 17170002.
24. Chen R, Li L, Butte AJ. AILUN: reannotating gene expression data automatically. Nat Methods 2007, 4(11):879. 10.1038/nmeth1107-879, 2716375, 17971777.
25. Sing T, Sander O, Beerenwinkel N, Lengauer T. ROCR: visualizing classifier performance in R. Bioinformatics 2005, 21(20):3940-3941. 10.1093/bioinformatics/bti623, 16096348.
26. Pollard KS, Dudoit S, van der Laan MJ. Multiple Testing Procedures: the multtest Package and Applications to Genomics. Bioinformatics and Computational Biology Solutions Using R and Bioconductor 2005, New York: Springer, Gentleman R, Carey VJ, Huber W, Irizarry RA, Dudoit S.
27. Carr D, Littlefield R, Nicholson W, Littlefield J. Scatterplot matrix techniques for large N. Journal of the American Statistical Association 1987, 424-436.