The DOI matches its Crossref record; 97 of the 99 references it cites were found in a registry or an index.
Microarray data analysis: from disarray to consolidation and consensus
Abstract
In just a few years, microarrays have gone from obscurity to being almost ubiquitous in biological research. At the same time, the statistical methodology for microarray analysis has progressed from simple visual assessments of results to a weekly deluge of papers that describe purportedly novel algorithms for analysing changes in gene expression. Although the many procedures that are available might be bewildering to biologists who wish to apply them, statistical geneticists are recognizing commonalities among the different methods. Many are special cases of more general models, and points of consensus are emerging about the general approaches that warrant use and elaboration.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The pooling strategy averages biological variations, increases statistical power, and reduces workload (Allison et al., 2006).”
From Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression (2020) · cites this paper as Allison et al., 2006
In the citing paper
“The pooling strategy averages biological variations, increases statistical power, and reduces workload (Allison et al., 2006).”
From Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression (2020) · cites this paper as Allison et al., 2006
In the citing paper
“The pooling strategy averages biological variations, increases statistical power, and reduces workload (Allison et al., 2006).”
From Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression (2020) · cites this paper as Allison et al., 2006
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
In silico prediction of protein-protein interactions in human macrophages
Souiai, O., Guerfali, F. Z., Miled, S. B., Brun, C., & Benkahla, A. (2014) · BMC Research Notes · doi:10.1186/1756-0500-7-157 · Cited by 10,785
Significance analysis of microarrays applied to the ionizing radiation response
Tusher, V. G., Tibshirani, R., & Chu, G. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.091062498 · Cited by 10,568
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Everitt, B. J., Landau, S., & Leese, M. (1974) · Cited by 9,186
Bolstad, B. M., Irizarry, R. A., Åstrand, M., & Speed, T. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.185 · Cited by 8,328
Summaries of Affymetrix GeneChip probe level data
Irizarry, R. A. (2003) · Nucleic Acids Research · doi:10.1093/nar/gng015 · Cited by 4,837
Yang, Y., Dudoit, S., Luu, P., Lin, D., Peng, V., Ngai, J., & Speed, T. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.4.e15 · Cited by 3,722
The positive false discovery rate: a Bayesian interpretation and the q-value
Storey, J. D. (2003) · The Annals of Statistics · doi:10.1214/aos/1074290335 · Cited by 2,204
Microarray data normalization and transformation
Quackenbush, J. (2002) · Nature Genetics · doi:10.1038/ng1032 · Cited by 1,975
Flagged first, then by citations
2 of the 99 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- Osier, M. V. in DNA Microarrays and Statistical Genomic Techniques: Design, Analysis, and Interpretation of Experiments (Marcel Dekker, New York, 2005).
- Dobbin, K. & Simon, R. Sample size determination in microarray experiments for class comparison and prognostic classification. Biostatistics 6, 27–38 (2005). · DOI
Cited by
Sorted by citations
phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data
McMurdie, P. J., & Holmes, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061217 · Cited by 21,942
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
GREAT improves functional interpretation of cis-regulatory regions
McLean, C. Y., Bristor, D., Hiller, M., Clarke, S. L., Schaar, B. T., Lowe, C. B., Wenger, A. M., & Bejerano, G. (2010) · Nature Biotechnology · doi:10.1038/nbt.1630 · Cited by 4,502
Waste Not, Want Not: Why Rarefying Microbiome Data Is Inadmissible
McMurdie, P. J., & Holmes, S. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003531 · Cited by 3,034
RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays
Marioni, J. C., Mason, C. E., Mane, S. M., Stephens, M., & Gilad, Y. (2008) · Genome Research · doi:10.1101/gr.079558.108 · Cited by 2,771
Tackling the widespread and critical impact of batch effects in high-throughput data
Leek, J. T., Scharpf, R. B., Bravo, H. C., Simcha, D., Langmead, B., Johnson, W. E., Geman, D., Baggerly, K., & Irizarry, R. A. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2825 · Cited by 2,196
Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation
Merico, D., Isserlin, R., Stueker, O., Emili, A., & Bader, G. D. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013984 · Cited by 2,235
Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells
Ramsköld, D., Luo, S., Wang, Y.-C., Li, R., Deng, Q., Faridani, O. R., Daniels, G. A., Khrebtukova, I., Loring, J. F., Laurent, L. C., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2282 · Cited by 1,609
Bock, C., Kiskinis, E., Verstappen, G., Gu, H., Boulting, G., Smith, Z. D., Ziller, M., Croft, G. F., Amoroso, M. W., Oakley, D. H., et al. (2011) · Cell · doi:10.1016/j.cell.2010.12.032 · Cited by 1,009
MAQC Consortium (2010) · Nature Biotechnology · doi:10.1038/nbt.1665 · Cited by 889
Analyzing gene expression data in terms of gene sets: methodological issues
Goeman, J. J., & Bühlmann, P. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm051 · Cited by 809
Vaske, C. J., Benz, S. C., Sanborn, J. Z., Earl, D., Szeto, C., Zhu, J., Haussler, D., & Stuart, J. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq182 · Cited by 786
Detection of gene pathways with predictive power for breast cancer prognosis
Ma, S., & Kosorok, M. R. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-1 · Cited by 693
Hill, J., Feuerer, M., Tash, K., Haxhinasto, S., Perez, J., Melamed, R., Mathis, D., & Benoist, C. (2007) · Immunity · doi:10.1016/j.immuni.2007.09.010 · Cited by 671
Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression
Bai, B., Wang, X., Li, Y., Chen, P.-C., Yu, K., Dey, K. K., Yarbro, J. M., Han, X., Lutz, B. M., Rao, S., et al. (2020) · Neuron · doi:10.1016/j.neuron.2019.12.015 · Cited by 565
“The pooling strategy averages biological variations, increases statistical power, and reduces workload (Allison et al., 2006).”
BackgroundClarke, R. C., Ressom, H. W., Wang, A., Xuan, J., Liu, M., Gehan, E. A., & Wang, Y. (2007) · Nature reviews. Cancer · doi:10.1038/nrc2294 · Cited by 623
Repeatability of published microarray gene expression analyses
Ioannidis, J. P. A., Allison, D. B., Ball, C. A., Coulibaly, I., Cui, X., Culhane, A. C., Falchi, M., Furlanello, C., Game, L., Jurman, G., et al. (2009) · Nature Genetics · doi:10.1038/ng.295 · Cited by 551
Self-citationAnalysing and interpreting DNA methylation data
Bock, C. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3273 · Cited by 600
Multi-omic and multi-view clustering algorithms: review and cancer benchmark
Rappoport, N., & Ron Shamir, A. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky889 · Cited by 570
Estavillo, G. M., Crisp, P. A., Phonphoem, W. P., Wirtz, M., Collinge, D., Carrie, C., Giraud, E., Whelan, J., David, P., Javot, H., et al. (2011) · The Plant Cell · doi:10.1105/tpc.111.091033 · Cited by 554
The effect of the alignment of electrospun fibrous scaffolds on Schwann cell maturation
Chew, S. Y., Mi, R., Höke, A., & Leong, K. W. (2007) · Biomaterials · doi:10.1016/j.biomaterials.2007.10.025 · Cited by 524
The molecular ecologist's guide to expressed sequence tags
Bouck, A. C., & Vision, T. (2006) · Molecular Ecology · doi:10.1111/j.1365-294x.2006.03195.x · Cited by 515
A Review of Ensemble Methods in Bioinformatics
Yang, P., Yang, Y. H., Zhou, B. B., & Zomaya, A. Y. (2010) · Current Bioinformatics · doi:10.2174/157489310794072508 · Cited by 516
Synthetic lethal screen identification of chemosensitizer loci in cancer cells
Whitehurst, A. W., Bodemann, B. O., Cardenas, J., Ferguson, D., Girard, L., Peyton, M., Minna, J. D., Michnoff, C. H., Hao, W., Roth, M. G., et al. (2007) · Nature · doi:10.1038/nature05697 · Cited by 471
Pineles, B. L., Romero, R., Montenegro, D., Tarca, A. L., Han, Y. M., Kim, Y. M., Draghici, S., Espinoza, J., Kusanovic, J. P., Mittal, P., et al. (2007) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2007.01.008 · Cited by 450
Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders
Parikshak, N. N., Gandal, M. J., & Geschwind, D. H. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3934 · Cited by 430
Comprehensive high-throughput arrays for relative methylation (CHARM)Preprint
Irizarry, R. A., Ladd‐Acosta, C., Carvalho, B. S., Wu, H., Brandenburg, S. A., Jeddeloh, J. A., Wen, B., & Feinberg, A. P. (2008) · Genome Research · doi:10.1101/gr.7301508 · Cited by 433
Rat toxicogenomic study reveals analytical consistency across microarray platforms
Guo, L., Lobenhofer, E. K., Wang, C., Shippy, R., Harris, S., Zhang, L., Mei, N., Chen, T., Herman, D., Goodsaid, F. M., et al. (2006) · Nature Biotechnology · doi:10.1038/nbt1238 · Cited by 408
Shi, L. M., Jones, W. D., Jensen, R. V., Harris, S., Perkins, R., Goodsaid, F. M., Guo, L., Croner, L. J., Boysen, C., Fang, H., et al. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-s9-s10 · Cited by 402
Sequeira, A., Mamdani, F., Ernst, C., Vawter, M. P., Bunney, W. E., Lebel, V., Rehal, S., Klempan, T., Gratton, A., Benkelfat, C., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0006585 · Cited by 388
Approaches for Extracting Practical Information from Gene Co-expression Networks in Plant Biology
Aoki, K., Ogata, Y., & Shibata, D. (2007) · Plant and Cell Physiology · doi:10.1093/pcp/pcm013 · Cited by 368
Transcriptomics in the RNA-seq era
McGettigan, P. (2013) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2012.12.008 · Cited by 383
Computational solutions for omics data
Berger, B., Peng, J., & Singh, M. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3433 · Cited by 353
Ng, S., Ivanova, A., Duncan, O., Law, S. R., Aken, O. V., Clercq, I. D., Wang, Y., Carrie, C., Lin, X., Kmiec, B., et al. (2013) · The Plant Cell · doi:10.1105/tpc.113.113985 · Cited by 346
Group Faultlines: A Review, Integration, and Guide to Future Research
Thatcher, S. M. B., & Patel, P. C. (2012) · Journal of Management · doi:10.1177/0149206311426187 · Cited by 391
Gene-set approach for expression pattern analysis
Nam, D., & Kim, S.-Y. (2008) · Briefings in Bioinformatics · doi:10.1093/bib/bbn001 · Cited by 338
Fold change and p-value cutoffs significantly alter microarray interpretations
Dalman, M. R., Deeter, A., Nimishakavi, G., & Duan, Z.-H. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-s2-s11 · Cited by 343
Rank-Based Inverse Normal Transformations are Increasingly Used, But are They Merited?
Beasley, T. M., Erickson, S. W., & Allison, D. B. (2009) · Behavior Genetics · doi:10.1007/s10519-009-9281-0 · Cited by 332
Self-citationGATHER: a systems approach to interpreting genomic signatures
Chang, J. T., & Nevins, J. R. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl483 · Cited by 315
Next-generation sequencing data interpretation: enhancing reproducibility and accessibility
Nekrutenko, A., & Taylor, J. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3305 · Cited by 328
Hematopoietic Fingerprints: An Expression Database of Stem Cells and Their Progeny
Chambers, S. M., Boles, N. C., Lin, K. K., Tierney, M., Bowman, T. V., Bradfute, S. B., Chen, A. J., Merchant, A. A., Sirin, O., Weksberg, D. C., et al. (2007) · Cell stem cell · doi:10.1016/j.stem.2007.10.003 · Cited by 322
Kohane, I. S., Masys, D. R., & Altman, R. B. (2006) · JAMA · doi:10.1001/jama.296.2.212 · Cited by 307
Identification of pediatric septic shock subclasses based on genome-wide expression profiling
Wong, H. R., Cvijanovich, N. Z., Lin, R., Allen, G. L., Thomas, N. J., Willson, D. F., Freishtat, R. J., ANAS, N. G., Meyer, K., Checchia, P. A., et al. (2009) · BMC Medicine · doi:10.1186/1741-7015-7-34 · Cited by 309
Analysis of microarray experiments of gene expression profiling
Tarca, A. L., Romero, R. J., & Drăghici, S. (2006) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2006.07.001 · Cited by 312
Zapala, M. A., & Schork, N. J. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609333103 · Cited by 296
Twine, N. A., Janitz, K., Wilkins, M. R., & Janitz, M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016266 · Cited by 309
Zakikhany, K., Naglik, J. R., Schmidt-Westhausen, A., Holland, G., Schaller, M., & Hube, B. (2007) · Cellular Microbiology · doi:10.1111/j.1462-5822.2007.01009.x · Cited by 288
Gene Expression Programs during Shoot, Root, and Callus Development in Arabidopsis Tissue Culture
Che, P., Lall, S., Nettleton, D. S., & Howell, S. H. (2006) · PLANT PHYSIOLOGY · doi:10.1104/pp.106.081240 · Cited by 270
The Metabolic Response of Heterotrophic Arabidopsis Cells to Oxidative Stress
Baxter, C., Redestig, H., Schauer, N., Repsilber, D., Patil, K. R., Nielsen, J., Selbig, J., Liu, J., Fernie, A. R., & Sweetlove, L. J. (2006) · PLANT PHYSIOLOGY · doi:10.1104/pp.106.090431 · Cited by 269
Pathway Analysis: State of the Art
García-Campos, M. A., Enríquez, J. E., & Lemus, E. H. (2015) · Frontiers in Physiology · doi:10.3389/fphys.2015.00383 · Cited by 292
Sartor, M. A., Tomlinson, C. R., Wesselkamper, S. C., Sivaganesan, S., Leikauf, G. D., & Medvedovic, M. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-538 · Cited by 263
Steibel, J. P., Poletto, R., Coussens, P. M., & Rosa, G. J. M. (2009) · Genomics · doi:10.1016/j.ygeno.2009.04.008 · Cited by 261
Rapid microRNA (miRNA) detection and classification via surface-enhanced Raman spectroscopy (SERS)
Driskell, J. D., Seto, A. G., Jones, L. P., Jokela, S. J., Dluhy, R. A., Zhao, Y., & Tripp, R. A. (2008) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2008.07.060 · Cited by 259
Pujol, N., Zugasti, O., Wong, D., Couillault, C., Kurz, C. L., Hinrich Schulenburg, Y., & Ewbank, J. J. (2008) · PLoS Pathogens · doi:10.1371/journal.ppat.1000105 · Cited by 258
Body fluid biomarkers in multiple sclerosis
Comabella, M., & Montalbán, X. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70233-3 · Cited by 268
Quantitative Analysis of the Intra- and Inter-Individual Variability of the Normal Urinary Proteome
Nagaraj, N., & Mann, M. (2010) · Journal of Proteome Research · doi:10.1021/pr100835s · Cited by 251
Assessing the human immune system through blood transcriptomics
Chaussabel, D., Pascual, V., & Banchereau, J. (2010) · BMC Biology · doi:10.1186/1741-7007-8-84 · Cited by 264
Álvarez, M., Schrey, A. W., & Richards, C. L. (2014) · Molecular Ecology · doi:10.1111/mec.13055 · Cited by 248
OMICtools: an informative directory for multi-omic data analysis
Henry, V., Bandrowski, A. E., Pepin, A.-S., Gonzalez, B. J., & Desfeux, A. (2014) · Database · doi:10.1093/database/bau069 · Cited by 236
Design and validation issues in RNA-seq experiments
Fang, Z., & Cui, X. (2011) · Briefings in Bioinformatics · doi:10.1093/bib/bbr004 · Cited by 243
Self-citationHsu, E., Shi, H., Jordan, R. M., Lyons‐Weiler, J., Pilewski, J. M., & Feghali‐Bostwick, C. A. (2010) · Arthritis & Rheumatism · doi:10.1002/art.30159 · Cited by 227
Rakhshandehroo, M., Sanderson, L. M., Matilainen, M., Stienstra, R., Carlberg, C., de Groot, P. J., Müller, M., & Kersten, S. (2007) · PPAR Research · doi:10.1155/2007/26839 · Cited by 241
Sexually divergent induction of microglial-associated neuroinflammation with hippocampal aging
Mangold, C. A., Wronowski, B., Du, M., Masser, D. R., Hadad, N., Bixler, G. V., Brucklacher, R. M., Ford, M. M., Sonntag, W. E., & Freeman, W. M. (2017) · Journal of Neuroinflammation · doi:10.1186/s12974-017-0920-8 · Cited by 203
Zayed, A., & Robinson, G. E. (2012) · Annual Review of Genetics · doi:10.1146/annurev-genet-110711-155517 · Cited by 218
Justé, A., Thomma, B. P. H. J., & Lievens, B. (2008) · Food Microbiology · doi:10.1016/j.fm.2008.04.009 · Cited by 211
Subrata, L. S., Bizzintino, J. A., Mamessier, É., Bosco, A., McKenna, K. L., Wikström, M. E., Goldblatt, J., Sly, P. D., Hales, B. J., Thomas, W. R., et al. (2009) · The Journal of Immunology · doi:10.4049/jimmunol.0900695 · Cited by 210
Τzouvelekis, Α., Harokopos, V., Paparountas, T., Oikonomou, N., Chatziioannou, A. A., Vilaras, G., Tsiambas, E., Karameris, A., Bouros, D. E., & Aidinis, V. (2007) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.200705-683oc · Cited by 209
Patterns of pain: Meta-analysis of microarray studies of pain
LaCroix‐Fralish, M. L., Austin, J., Zheng, F. Y., Levitin, D. J., & Mogil, J. S. (2011) · Pain · doi:10.1016/j.pain.2011.04.014 · Cited by 204
Wong, D., Bazopoulou, D., Pujol, N., Tavernarakis, N., & Ewbank, J. J. (2007) · Genome biology · doi:10.1186/gb-2007-8-9-r194 · Cited by 203
The characteristic direction: a geometrical approach to identify differentially expressed genes
Clark, N. R., Hu, K. S., Feldmann, A. S., Kou, Y., Chen, E. Y., Duan, Q., & Ma’ayan, A. (2014) · BMC Bioinformatics · doi:10.1186/1471-2105-15-79 · Cited by 204
Peatman, E., Baoprasertkul, P., Terhune, J. S., Xu, P., Nandi, S., Kucuktas, H., Li, P., Wang, S., Somridhivej, B., Dunham, R. A., et al. (2007) · Developmental & Comparative Immunology · doi:10.1016/j.dci.2007.03.003 · Cited by 199
Transcript profiling in host-pathogen interactions.
Wise, R., Moscou, M., Bogdanove, A., & Whitham, S. (2007) · Annual Review of Phytopathology · doi:10.1146/annurev.phyto.45.011107.143944 · Cited by 185
An estimate of the science-wise false discovery rate and application to the top medical literature
Jager, L. R., & Leek, J. T. (2014) · Biostatistics · doi:10.1093/biostatistics/kxt007 · Cited by 179
Stability and aggregation of ranked gene lists
Boulesteix, A., & Slawski, M. (2009) · Briefings Bioinform. · doi:10.1093/bib/bbp034 · Cited by 192
No Control Genes Required: Bayesian Analysis of qRT-PCR Data
Matz, M. V., Wright, R. M., & Scott, J. G. (2013) · PLoS ONE · doi:10.1371/journal.pone.0071448 · Cited by 177
Outlier sums for differential gene expression analysis
Tibshirani, R., & Hastie, T. J. (2006) · Biostatistics · doi:10.1093/biostatistics/kxl005 · Cited by 175
Survival analysis with high-dimensional covariates
Witten, D., & Tibshirani, R. J. (2009) · Statistical Methods in Medical Research · doi:10.1177/0962280209105024 · Cited by 172
Gene profiling in white blood cells predicts infliximab responsiveness in rheumatoid arthritis
Lequerré, T., Gauthier-Jauneau, A.-C., Bansard, C., Derambure, C., Hiron, M., Vittecoq, O., Daveau, M., Mejjad, O., Daragon, A., Tron, F., et al. (2006) · Arthritis Research & Therapy · doi:10.1186/ar1990 · Cited by 168
The role of gene expression in ecological speciation
Pavey, S. A., Collin, H., Nosil, P., & Rogers, S. M. (2010) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2010.05765.x · Cited by 173
Data Analysis Strategies in Medical Imaging
Parmar, C., Barry, J. D., Hosny, A., Quackenbush, J. F., & Aerts, H. J. W. L. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-18-0385 · Cited by 163
Statistical methods for gene set co-expression analysis
Choi, Y., & Kendziorski, C. M. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp502 · Cited by 162
Cyber-T web server: differential analysis of high-throughput data
Kayala, M. A., & Baldi, P. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks420 · Cited by 160
VanGuilder, H. D., Yan, H., Farley, J. A., Sonntag, W. E., & Freeman, W. M. (2010) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.2010.06719.x · Cited by 154
Jeanmougin, M., de Reyniès, A., Marisa, L., Paccard, C., Nuel, G., & Guedj, M. (2010) · PLoS ONE · doi:10.1371/journal.pone.0012336 · Cited by 162
Fox, E. M., Miller, T. W., Balko, J. M., Kuba, M. G., Sanchez, V. M., Smith, R. A., Liu, S., Gonzalez-Angulo, A. M., Mills, G. B., Ye, F., et al. (2011) · Cancer Research · doi:10.1158/0008-5472.can-11-1295 · Cited by 154
van Straten, E. M. E., Bloks, V. W., Huijkman, N., Baller, J. F. W., van Meer, H., Lütjohann, D., Kuipers, F., & Plösch, T. (2009) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.00413.2009 · Cited by 151
NORMA-Gene: A simple and robust method for qPCR normalization based on target gene data
Heckmann, L., Sørensen, P. B., Krogh, P. H., & Sørensen, J. G. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-250 · Cited by 151
Adler, P., Kolde, R., Kull, M., Tkachenko, A., Peterson, H., Reimand, J., & Vilo, J. (2009) · Genome biology · doi:10.1186/gb-2009-10-12-r139 · Cited by 151
Group testing for pathway analysis improves comparability of different microarray datasets
Manoli, T., Gretz, N., Gröne, H., Kenzelmann, M., Eils, R., & Brors, B. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl424 · Cited by 150
A Genomic Approach to Human Autoimmune Diseases
Pascual, V., Chaussabel, D., & Banchereau, J. (2010) · Annual Review of Immunology · doi:10.1146/annurev-immunol-030409-101221 · Cited by 152
Patterns of Positive Selection in Seven Ant Genomes
Roux, J., Privman, E., Moretti, S., Daub, J. T., Robinson‐Rechavi, M., & Keller, L. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu141 · Cited by 146
A scalable method for integration and functional analysis of multiple microarray datasets
Huttenhower, C., Hibbs, M., Myers, C. L., & Troyanskaya, O. G. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl492 · Cited by 144
Molecular signatures from omics data: From chaos to consensus
Sung, J., Wang, Y., Chandrasekaran, S., Witten, D., & Price, N. D. (2012) · Biotechnology Journal · doi:10.1002/biot.201100305 · Cited by 142
Hayes, E. T., Wilks, J. C., Sanfilippo, P., Yohannes, E., Tate, D. P., Jones, B. D., Radmacher, M. D., BonDurant, S. S., & Slonczewski, J. L. (2006) · BMC Microbiology · doi:10.1186/1471-2180-6-89 · Cited by 140
Zhao, L., Dong, Q., Luo, C., Wu, Y., Bu, D., Qi, X., Luo, Y., & Zhao, Y. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.04.067 · Cited by 127
Shi, L. M., Perkins, R., Fang, H., & Tong, W. (2008) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2007.11.003 · Cited by 139
Gene set analysis of SNP data: benefits, challenges, and future directions
Fridley, B. L., & Biernacka, J. M. (2011) · European Journal of Human Genetics · doi:10.1038/ejhg.2011.57 · Cited by 146
Wen, Z., Wang, Z. K., Wang, S., Ravula, R., Yang, L., Xu, J., Wang, C., Zuo, Z., Chow, M. S. S., Shi, L. M., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018278 · Cited by 136
Queiroz, R., Benz, C., Fellenberg, K., Hoheisel, J. D., & CLAYTON, C. E. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-495 · Cited by 138
Green, C. E., Liu, T., Montel, V., Hsiao, G., Lester, R. D., Subramaniam, S., Gonias, S. L., & Klemke, R. L. (2009) · PLoS ONE · doi:10.1371/journal.pone.0006713 · Cited by 133
Metadata
- Authors
- Allison, D. B., Cui, X., Page, G. P., & Sabripour, M.
- Affiliations
- University of Alabama (US)
- Corresponding author
- Allison, David B.
- Venue
- Nature Reviews Genetics
- Published
- 2006-01-01
- Volume
- 7
- Issue
- 1
- Pages
- 55-65
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- OpenAlex
- W2021129827
- Semantic Scholar
- 7aeace2306487c5e5f3ff6711e1a5d3fc1e4c899
- Cited by
- 1,339
- References
- 99
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 10 · 2023: 13 · 2022: 19 · 2021: 23 · 2020: 35 · 2019: 35 · 2018: 43 · 2017: 56 · 2016: 48 · 2015: 68 · 2014: 73 · 2013: 69 · 2012: 104
- FWCI
- 9.79
- Type
- journal article
- Language
- en
- Update notices
- erratum (2006-05-01)
- Open access
- closed
- Locations
- Nature Reviews Genetics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- U.S. Department of Defense
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- microarray data analysis, gene expression analysis, statistical analysis, normalization, differential gene expression, consensus methods, reproducibility
- MeSH terms
- Algorithms, Computer Simulation, Data Interpretation, Statistical, Gene Expression Regulation, Genetic Techniques, Genetics, Humans, Models, Biological, RNA, Messenger, Models, Statistical, Cluster Analysis, DNA, Complementary, Computational Biology, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Microarray Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review