Removing batch effects for prediction problems with frozen surrogate variable analysis

PeerJ

Volumn 2014, Issue 1, 2014, Pages

  Parker, Hilary S ^a   Bravo, Héctor Corrada ^b   Leek, Jeffrey T ^a  

^a JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^b Institute of Advanced Computer Science   (United States)

Author keywords

Batch effects; Database; Genomics; Machine learning; Prediction; Statistics; Surrogate variable analysis

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; BATCH EFFECT CORRECTION; DNA METHYLATION; FROZEN SURROGATE VARIABLE ANALYSIS ALGORITHM; GENE EXPRESSION; MICROARRAY ANALYSIS; PREDICTION; QUALITY CONTROL PROCEDURES; RNA SEQUENCE; SIMULATION;

EID: 84907704976     PISSN: None     EISSN: 21678359     Source Type: Journal    
DOI: 10.7717/peerj.561     Document Type: Article

References (33)

1. Akey JM, Biswas S, Leek JT, Storey JD. 2007. On the design and analysis of gene expression studies in human populations. Nature Genetics 39(7):807-808 DOI 10.1038/ng0707-807
2. Baggerly KA, Morris JS, Coombes KR. 2004. Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments. Bioinformatics 20(5):777-785 DOI 10.1093/bioinformatics/btg484
3. Baggerly KA, Coombes KR, Morris JS. 2003. Bias, randomization, and ovarian proteomic data: a reply to "producers and consumers". Cancer Informatics 1:9-14
4. Buja A, Eyuboglu N. 1992. Remarks on parallel analysis. Multivariate Behavioral Research 27(4):509-540 DOI 10.1207/s15327906mbr2704 2
5. Chan IS, Ginsburg GS. 2011. Personalized medicine: progress and promise. Annual Review of Genomics and Human Genetics 12:217-244 DOI 10.1146/annurev-genom-082410-101446
6. Chikina MD, Sealfon SC. 2014. Increasing consistency of disease biomarker prediction across datasets. PLoS ONE 9(4):e91272 DOI 10.1371/journal.pone.0091272
7. Edgar R, Domrachev M, Lash AE. 2002. Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Research 30(1):207-210 DOI 10.1093/nar/30.1.207
8. Efron B. 2004. Large-scale simultaneous hypothesis testing. Journal of the American Statistical Association 99(465):96-104 DOI 10.1198/016214504000000089
9. Eisen MB, Spellman PT, Brown PO, Botstein D. 1998. Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences of the United States of America 95(25):14863-14868 DOI 10.1073/pnas.95.25.14863
10. Fare TL, Coffey EM, Dai H, He YD, Kessler DA, Kilian KA, Koch JE, LeProust E, Marton MJ, Meyer MR, Stoughton RB, Tokiwa GY, Wang Y. 2003. Effects of atmospheric ozone on microarray data quality. Analytical Chemistry 75(17):4672-4675 DOI 10.1021/ac034241b
11. Friguet C, Kloareg M, Causeur D. 2009. A factor model approach to multiple testing under dependence. Journal of the American Statistical Association 104(488):1406-1415 DOI 10.1198/jasa.2009.tm08332
12. Gagnon-Bartsch JA, Speed TP. 2012. Using control genes to correct for unwanted variation in microarray data. Biostatistics 13(3):539-552 DOI 10.1093/biostatistics/kxr034
13. Jaffe AE, Murakami P, Lee H, Leek JT, Fallin MD, Feinberg AP, Irizarry RA. 2012. Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies. International Journal of Epidemiology 41(1):200-209 DOI 10.1093/ije/dyr238
14. Johnson WE, Li C, Rabinovic A. 2007. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8(1):118-127 DOI 10.1093/biostatistics/kxj037
15. Lambert CG, Black LJ. 2012. Learning from our GWAS mistakes: from experimental design to scientific method. Biostatistics 13(2):195-203 DOI 10.1093/biostatistics/kxr055
16. Lander ES. 1999. Array of hope. Nature Genetics 21(1 Suppl):3-4 DOI 10.1038/4427
17. Leek JT. 2011. Asymptotic conditional singular value decomposition for high-dimensional genomic data. Biometrics 67(2):344-352 DOI 10.1111/j.1541-0420.2010.01455.x
18. Leek J. 2014. svaseq: removing batch effects and other unwanted noise from sequencing data bioRxiv DOI 10.1101/006585
19. Leek JT, Storey JD. 2007. Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genetics 3(9):1724-1735 DOI 10.1371/journal.pgen.0030161
20. Leek JT, Storey JD. 2008. A general framework for multiple testing dependence. Proceedings of the National Academy of Sciences of the United States of America 105(48):18718-18723 DOI 10.1073/pnas.0808709105
21. Leek JT, Johnson WE, Parker HS, Jaffe AE, Storey JD. 2012. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics 28(6):882-883 DOI 10.1093/bioinformatics/bts034
22. Leek JT, Scharpf RB, Bravo HC, Simcha D, Langmead B, Johnson WE, Geman D, Baggerly KA, Irizarry RA. 2010. Tackling the widespread and critical impact of batch effects in high-throughput data. Nature Reviews Genetics 11(10):733-739 DOI 10.1038/nrg2825
23. Luo J, Schumacher M, Scherer A, Sanoudou D, Megherbi D, Davison T, Shi T, Tong W, Shi L, Hong H, Zhao C, Elloumi F, Shi W, Thomas R, Lin S, Tillinghast G, Liu G, Zhou Y, Herman D, Li Y, Deng Y, Fang H, Bushel P, Woods M, Zhang J. 2010. A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data. The Pharmacogenomics Journal 10(4):278-291 DOI 10.1038/tpj.2010.57
24. Micheel CM, Nass SJ, Omenn GS (eds.) 2012. Evolution of translational omics: lessons learned and the path forward. Washington, DC: National Academies Press
25. Parker HS, Leek JT. 2012. The practical effect of batch on genomic prediction. Statistical Applications in Genetics and Molecular Biology 11(3):1-22 DOI 10.1515/1544-6115.1766
26. Scharpf RB, Ruczinski I, Carvalho B, Doan B, Chakravarti A, Irizarry RA. 2011. A multilevel model to address batch effects in copy number estimation using SNP arrays. Biostatistics 12(1):33-50 DOI 10.1093/biostatistics/kxq043
27. Sebastiani P, SolovieffN, Puca A, Hartley SW, Melista E, Andersen S, Dworkis DA, Wilk JB, Myers RH, Steinberg MH, Montano M, Baldwin CT, Perls TT. 2011. Science 333(6041):404 DOI 10.1126/science.333.6041.404-a
28. Spielman RS, Bastone LA, Burdick JT, Morley M, Ewens WJ, Cheung VG. 2007. Common genetic variants account for differences in gene expression among ethnic groups. Nature Genetics 39(2):226-331 DOI 10.1038/ng1955
29. Storey JD, Akey JM, Kruglyak L. 2005. Multiple locus linkage analysis of genomewide expression in yeast. PLoS Biology 3(8):e267 DOI 10.1371/journal.pbio.0030267
30. Tibshirani R, Hastie T, Narasimhan B, Chu G. 2002. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proceedings of the National Academy of Sciences of the United States of America 99(10):6567-6572 DOI 10.1073/pnas.082099299
31. Walker WL, Liao IH, Gilbert DL, Wong B, Pollard KS, McCulloch CE, Lit L, Sharp FR. 2008 Empirical Bayes accomodation of batch-effects in microarray data using identical replicate reference samples: application to RNA expression profiling of blood from Duchenne muscular dystrophy patients. BMC Genomics 9:494 DOI 10.1186/1471-2164-9-494
32. Warmuth MK, Kuzmin D. 2007. Randomized PCA algorithms with regret bounds that are logarithmic in the dimension. Advances in Neural Information Processing Systems 19:1481-1488
33. Warmuth MK, Kuzmin D. 2008. Randomized online PCA algorithms with regret bounds that are logarithmic in the dimension 9: 2287-2320