Missing value imputation for microarray data: A comprehensive comparison study and a web tool

BMC Systems Biology

Volumn 7, Issue , 2013, Pages

  Chiu, Chia Chun ^a   Chan, Shih Yao ^a   Wang, Chung Ching ^a   Wu, Wei Sheng ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BIOLOGY; BIOSTATISTICS; COMPARATIVE STUDY; DNA MICROARRAY; GENETICS; HUMAN; INTERNET; METHODOLOGY; SACCHAROMYCES CEREVISIAE; STATISTICAL MODEL; TIME;

ALGORITHMS; BIOSTATISTICS; COMPUTATIONAL BIOLOGY; HUMANS; INTERNET; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SACCHAROMYCES CEREVISIAE; TIME FACTORS;

EID: 84908547508     PISSN: None     EISSN: 17520509     Source Type: Journal    
DOI: 10.1186/1752-0509-7-S6-S12     Document Type: Article

References (47)

1. Wu W, Li W, Chen B: Computational reconstruction of transcriptional regulatory modules of the yeast cell cycle. BMC Bioinformatics 2006, 7:421
2. Rowicka M, Kudlicki A, Tu B, Otwinowski Z: High-resolution timing of cell cycle-regulated gene expression. Proc Natl Acad Sci USA 2007, 104:16892-16897
3. Wu W, Li W, Chen B: Identifying regulatory targets of cell cycle transcription factors using gene expression and ChIP-chip data. BMC Bioinformatics 2007, 8:188
4. Futschik M, Herzel H: Are we overestimating the number of cell-cycling genes? The impact of background models on time-series analysis. Bioinformatics 2008, 24:1063-1069
5. Wu W, Li W: Systematic identification of yeast cell cycle transcription factors using multiple data sources. BMC Bioinformatics 2008, 9:522
6. Siegal-Gaskins D, Ash J, Crosson S: Model-based deconvolution of cell cycle time-series data reveals gene expression details at high resolution. PLoS Comput Biol 2009, 5:e1000460
7. Wang H, Wang Y, Wu W: Yeast cell cycle transcription factors identification by variable selection criteria. Gene 2011, 485:172-176
8. Gasch A, Spellman P, Kao C, Carmel-Harel O, Eisen M, Storz G, Botstein D, Brown P: Genomic expression programs in the response of yeast cells to environmental changes. Mol Biol Cell 2000, 11:4241-4257
9. Wu W, Li W: Identifying gene regulatory modules of heat shock response in yeast. BMC Genomics 2008, 9:439
10. de Brevern AG, Hazout S, Malpertuy A: Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering. BMC Bioinformatics 2004, 5:114
11. Jörnsten R, Wang HY, Welsh WJ, Ouyang M: DNA microarray data imputation and significance analysis of differential expression. Bioinformatics 2005, 21(22):4155-4161
12. Scheel I, Aldrin M, Glad IK, Sørum R, Lyng H, Frigessi A: The influence of missing value imputation on detection of differentially expressed genes from microarray data. Bioinformatics 2005, 21(23):4272-4279
13. Sehgal MSB, Gondal I, Dooley LS, Coppel R: How to improve postgenomic knowledge discovery using imputation. EURASIP Journal on Bioinformatics and Systems Biology 2009, 2009:717136
14. Zhang Y, Xuan J, Reyes BGdl, Clarke R, Ressom HW: Reverse engineering module networks by PSO-RNN hybrid modeling. BMC Genomics 2009, 10(Suppl 1):S15
15. Wang D, Lv Y, Guo Z, Li X, Li Y, Zhu J, Yang D, Xu J, Wang C, Rao S, Yang B: Effects of replacing the unreliable cDNA microarray measurements on the disease classification based on gene expression profiles and functional modules. Bioinformatics 2006, 22(23):2883-2889
16. Ouyang M, Welsh WJ, Georgopoulos P: Gaussian mixture clustering and imputation of microarray data. Bioinformatics 2004, 20(6):917-923
17. Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D, Altman RB: Missing value estimation methods for DNA microarrays. Bioinformatics (Oxford, England) 2001, 17(6):520-525
18. Liew AWC, Law NF, Yan H: Missing value imputation for gene expression data: computational techniques to recover missing data from available information. Briefings in bioinformatics 2011, 12(5):498-513
19. Moorthy K, Mohamad MS, Deris S: A review on missing value imputation algorithms for microarray gene expression data. Advance in Bioinformatics 2013
20. Brãs LP, Menezes JC: Improving cluster-based missing value estimation of DNA microarray data. Biomolecular engineering 2007, 24(2):273-282
21. Kim KY, Kim BJ, Yi GS: Reuse of imputed data in microarray analysis increases imputation efficiency. BMC Bioinformatics 2004, 5:160
22. Bø TH, Dysvik B, Jonassen I: LSimpute: accurate estimation of missing values in microarray data with least squares methods. Nucleic Acids Research 2004, 32(3):e34
23. Kim H, Golub GH, Park H: Missing value estimation for DNA microarray gene expression data: local least squares imputation. Bioinformatics 2005, 21(2):187-198
24. Cai Z, Heydari M, Lin G: Iterated local least squares microarray missing value imputation. Journal of bioinformatics and computational biology 2006, 4(5):935-957
25. Zhang X, Song X, Wang H, Zhang H: Sequential local least squares imputation estimating missing value of microarray data. Computers in biology and medicine 2008, 38(10):1112-1120
26. Oba S, Sato Ma, Takemasa I, Monden M, Matsubara Ki, Ishii S: A Bayesian missing value estimation method for gene expression profile data. Bioinformatics 2003, 19(16):2088-2096
27. Jelizarow M, Guillemot V, Tenenhaus A, Strimmer K, Boulesteix AL: Overoptimism in bioinformatics: an illustration. Bioinformatics 2010, 26(16):1990-1998
28. Gan X, Liew AWC, Yan H: Microarray missing data imputation based on a set theoretic framework and biological knowledge. Nucleic Acids Research 2006, 34(5):1608-1619
29. Xiang Q, Dai X, Deng Y, He C, Wang J, Feng J, Dai Z: Missing value imputation for microarray gene expression data using histone acetylation information. BMC Bioinformatics 2008, 9:252
30. Johansson P, Häkkinen J: Improving missing value imputation of microarray data by using spot quality weights. BMC Bioinformatics 2006, 7:306
31. Hu J, Li H, Waterman MS, Zhou XJ: Integrative missing value estimation for microarray data. BMC Bioinformatics 2006, 7:449
32. Brock GN, Shaffer JR, Blakesley RE, Lotz MJ, Tseng GC: Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes. BMC Bioinformatics 2008, 9:12
33. Tuikkala J, Elo LL, Nevalainen OS, Aittokallio T: Missing value imputation improves clustering and interpretation of gene expression microarray data. BMC Bioinformatics 2008, 9:202
34. Celton M, Malpertuy A, Lelandais G, Brevern AGd: Comparative analysis of missing value imputation methods to improve clustering and interpretation of microarray experiments. BMC Genomics 2010, 11:15
35. Rao SSS, Shepherd LA, Bruno AE, Liu S, Miecznikowski JC: Comparing imputation procedures for Affymetrix gene expression datasets using MAQC datasets. Current Bioinformatics 2013
36. Spellman PT, Sherlock G, Zhang MQ, Iyer VR, Anders K, Eisen MB, Brown PO, Botstein D, Futcher B: Comprehensive identification of cell cycleregulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Molecular Biology of the Cell 1998, 9(12):3273-3297
37. Shapira M, Segal E, Botstein D: Disruption of yeast forkhead-associated cell cycle transcription by oxidative stress. Molecular Biology of the Cell 2004, 15(12):5659-5669
38. Whitfield ML, Sherlock G, Saldanha AJ, Murray JI, Ball CA, Alexander KE, Matese JC, Perou CM, Hurt MM, Brown PO, Botstein D: Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Molecular biology of the cell 2002, 13(6):1977-2000
39. Ogawa N, DeRisi J, Brown PO: New components of a system for phosphate accumulation and polyphosphate metabolism in Saccharomyces cerevisiae revealed by genomic expression analysis. Molecular biology of the cell 2000, 11(12):4309-4321
40. Bohen SP, Troyanskaya OG, Alter O, Warnke R, Botstein D, Brown PO, Levy R: Variation in gene expression patterns in follicular lymphoma and the response to rituximab. Proceedings of the National Academy of Sciences of the United States of America 2003, 100(4):1926-1930
41. Alizadeh AA, Eisen MB, Davis RE, Ma C, Lossos IS, Rosenwald A, Boldrick JC, Sabet H, Tran T, Yu X, Powell JI, Yang L, Marti GE, Moore T, Hudson JJ, Lu L, Lewis DB, Tibshirani R, Sherlock G, Chan WC, Greiner TC, Weisenburger DD, Armitage JO, Warnke R, Levy R, Wilson W, Grever MR, Byrd JC, Botstein D, Brown PO, Staudt LM: Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000, 403(6769):503-511
42. Baldwin DN, Vanchinathan V, Brown PO, Theriot JA: A gene-expression program reflecting the innate immune response of cultured intestinal epithelial cells to infection by Listeria monocytogenes. Genome Biology 2002, 4:R2
43. Yoshimoto H, Saltsman K, Gasch AP, Li HX, Ogawa N, Botstein D, Brown PO, Cyert MS: Genome-wide analysis of gene expression regulated by the calcineurin/Crz1p signaling pathway in Saccharomyces cerevisiae. The Journal of biological chemistry 2002, 277(34):31079-31088
44. Brauer MJ, Saldanha AJ, Dolinski K, Botstein D: Homeostatic adjustment and metabolic remodeling in glucose-limited yeast cultures. Molecular Biology of the Cell 2005, 16(5):2503-2517
45. Ronen M, Botstein D: Transcriptional response of steady-state yeast cultures to transient perturbations in carbon source. Proceedings of the National Academy of Sciences of the United States of America 2006, 103(2):389-394
46. Sehgal MSB, Gondal I, Dooley LS: Collateral missing value imputation: a new robust missing value estimation algorithm for microarray data. Bioinformatics (Oxford, England) 2005, 21(10):2417-2423
47. Oh S, Kang DD, Brock GN, Tseng GC: Biological impact of missing-value imputation on downstream analyses of gene expression profiles. Bioinformatics 2011, 27:78-86