Using control genes to correct for unwanted variation in microarray data

Biostatistics

Volumn 13, Issue 3, 2012, Pages 539-552

  Gagnon Bartsch, Johann A ^a   Speed, Terence P ^a,b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b WALTER AND ELIZA HALL INSTITUTE OF MEDICAL RESEARCH   (Australia)

Author keywords

Batch effect; Control gene; Differential expression; Factor analysis; SVA; Unwanted variation

Indexed keywords

ARTICLE; DNA MICROARRAY; FEMALE; GENE EXPRESSION PROFILING; HUMAN; MALE; METHODOLOGY; STATISTICAL ANALYSIS;

DATA INTERPRETATION, STATISTICAL; FEMALE; GENE EXPRESSION PROFILING; HUMANS; MALE; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS;

EID: 84862250978     PISSN: 14654644     EISSN: 14684357     Source Type: Journal    
DOI: 10.1093/biostatistics/kxr034     Document Type: Article

References (28)

1. ALTER, O., BROWN, P. O. AND BOTSTEIN, D. (2000). Singular value decomposition for genome-wide expression data processing and modeling. Proceedings of the National Academy of Sciences of the United States of America 97, 10101-10106.
2. BISHOP, C. M. (2006). Pattern Recognition and Machine Learning. New York: Springer.
3. BOLSTAD, B., COLLIN, F., BRETTSCHNEIDER, J., SIMPSON, K., COPE, L., IRIZARRY, R. AND SPEED, T. P. (2005). Quality assessment of Affymetrix GeneChip data. In: Gentleman, R., Carey, V., Huber,W., Irizarry, R. and Dudoit, S. (editors), Bioinformatics and Computational Biology Solutions Using R and Bioconductor. New York: Springer, pp. 33-47.
4. BOLSTAD, B. M., IRIZARRY, R. A., ASTRAND, M. AND SPEED, T. P. (2003). A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19, 185-193. (Pubitemid 36181903)
5. BRETTSCHNEIDER, J., COLLIN, F., BOLSTAD, B. M. AND SPEED, T. P. (2008). Quality assessment for short oligonucleotide microarray data. Technometrics 50, 241-264.
6. EISENBERG, E. AND LEVANON, E. Y. (2003). Human housekeeping genes are compact. Trends in Genetics 19, 362-365. (Pubitemid 36794535)
7. HUBERT, M., ROUSSEEUW, P. J. AND VANDEN BRANDEN, K. (2005). ROBPCA: a new approach to robust principal component analysis. Technometrics 47, 64-79. (Pubitemid 40213976)
8. IRIZARRY, R. A., BOLSTAD, B. M., COLLIN, F., COPE, L. M., HOBBS, B. AND SPEED, T. P. (2003). Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Research 31, e15.
9. IRIZARRY, R. A., HOBBS, B., COLLIN, F., BEAZER-BARCLAY, Y. D., ANTONELLIS, K. J., SCHERF, U. AND SPEED, T. P. (2003). Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249.
10. JOHNSON, W. E., LI, C. AND RABINOVIC, A. (2007). Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118-127. (Pubitemid 44906106)
11. KANG, H. M., SUL, J. H., SERVICE, S. K., ZAITLEN, N. A., KONG, S. Y., FREIMER, N. B., SABATTI, C. AND ESKIN, E. (2010). Variance component model to account for sample structure in genome-wide association studies. Nature Genetics 42, 348-354.
12. KANG, H. M., YE, C. AND ESKIN, E. (2008). Accurate discovery of expression quantitative trait loci under confounding from spurious and genuine regulatory hotspots. Genetics 180, 1909-1925.
13. KANG, H. M., ZAITLEN, N. A., WADE, C. M., KIRBY, A., HECKERMAN, D., DALY, M. J. AND ESKIN, E. (2008). Efficient control of population structure in model organism association mapping. Genetics 178, 1709-1723.
14. LEEK, J. T., SCHARPF, R. B., BRAVO, H. C., SIMCHA, D., LANGMEAD, B., JOHNSON, W. E., GEMAN, D., BAGGERLY, K. AND IRIZARRY, R. A. (2010). Tackling the widespread and critical impact of batch effects in high-throughput data. Nature Reviews Genetics 11, 733-739.
15. LEEK, J. T. AND STOREY, J. D. (2007). Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genetics 3, e161.
16. LEEK, J. T. AND STOREY, J. D. (2008). A general framework for multiple testing dependence. Proceedings of the National Academy of Sciences of the United State of America 105, 18718-18723.
17. LIPPA, K. A., DUEWER, D. L., SALIT, M. L., GAME, L. AND CAUSTON, H. C. (2010). Exploring the use of internal and external controls for assessing microarray technical performance. BMC Research Notes 3:349.
18. LISTGARTEN, J., KADIE, C., SCHADT, E. E. AND HECKERMAN, D. (2010). Correction for hidden confounders in the genetic analysis of gene expression. Proceedings of the National Academy of Sciences of the United States of America 107, 16465-16470.
19. LUCAS, J., CARVALHO, C., WANG, Q., BILD, A., NEVINS, J. AND WEST, M. (2006). Sparse statistical modelling in gene expression genomics. In: Do, K., Muller, P. and Vannucci, M. (editors), Bayesian Inference for Gene Expression and Proteomics. New York: Cambridge University Press, pp. 155-176.
20. MECHAM, B. H., NELSON, P. S. AND STOREY, J. D. (2010). Supervised normalization of microarrays. Bioinformatics 26, 1308-1315.
21. NIELSEN, T. O., WEST, R. B., LINN, S. C., ALTER, O., KNOWLING, M. A., O'CONNELL, J. X., ZHU, S., FERO, M., SHERLOCK, G., POLLACK, J. R. and others (2002). Molecular characterisation of soft tissue tumours: a gene expression study. The Lancet 359, 1301-1307. (Pubitemid 34310636)
22. PRICE, A. L., PATTERSON, N. J., PLENGE, R. M., WEINBLATT, M. E., SHADICK, N. A. AND REICH, D. (2006). Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics 38, 904-909. (Pubitemid 44141658)
23. SCHERER, A. (2009). Batch Effects and Noise in Microarray Experiments: Sources and Solutions. Chichester, UK: Wiley.
24. SMYTH, G. K. (2004). Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology 3:3.
25. STAMOVA, B. S., APPERSON, M., WALKER, W. L., TIAN, Y., XU, H., ADAMCZY, P., ZHAN, X., LIU, D. Z., ANDER, B. P., LIAO, I. H. and others (2009). Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood. BMC Medical Genomics 2:49.
26. STEGLE, O., KANNAN, A., DURBIN, R. AND WINN, J. (2008). Accounting for non-genetic factors improves the power of eQTL studies. Proceedings of the 12th Annual International Conference on Research in Computational Molecular Biology, 4995, 411-422.
27. VAWTER, M. P., EVANS, S., CHOUDARY, P., TOMITA, H., MEADOR-WOODRUFF, J., MOLNAR, M., LI, J., LOPEZ, J. F., MYERS, R., COX, D. and others (2004). Gender-specific gene expression in post-mortem human brain: localization to sex chromosomes. Neuropsychopharmacology 29, 373-384. (Pubitemid 38175155)
28. YU, J., PRESSOIR, G., BRIGGS, W. H., BI, I. V., YAMASAKI, M., DOEBLEY, J. F., MCMULLEN, M. D., GAUT, B. S., NIELSEN, D. M., HOLLAND, J. B. and others (2005). A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics 38, 203-208. (Pubitemid 43177234)