Empirical Bayes analysis of a microarray experiment

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 · see citing works

Cluster analysis and display of genome-wide expression patterns

Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14863 · Cited by 12,617 · see citing works

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 · see citing works

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 · see citing works

Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling

Alizadeh, A. A., Eisen, M. B., Davis, R. E., Ma, C., Lossos, I. S., Rosenwald, A., Boldrick, J. C., Sabet, H., Tran, T., Yu, X., et al. (2000) · Nature · doi:10.1038/35000501 · Cited by 9,925 · see citing works

Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection.

Li, C., & Wong, W. H. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.1.31 · Cited by 3,133 · see citing works

STATISTICAL METHODS FOR IDENTIFYING DIFFERENTIALLY EXPRESSED GENES IN REPLICATED cDNA MICROARRAY EXPERIMENTS

Dudoit, S., Yang, J. Y. H., Callow, M. J., & Speed, T. P. (2002) · Cited by 1,392 · see citing works

Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations

Lee, M. T., Kuo, F. C., Whitmore, G. A., & Sklar, J. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.18.9834 · Cited by 861 · see citing works

On Differential Variability of Expression Ratios: Improving Statistical Inference about Gene Expression Changes from Microarray Data

Newton, M. A., Kendziorski, C. M., Richmond, C. S., Blattner, F. R., & Tsui, K. (2001) · Journal of Computational Biology · doi:10.1089/106652701300099074 · Cited by 739 · see citing works

Bootstrapping cluster analysis: Assessing the reliability of conclusions from microarray experiments

Kerr, M. K., & Churchill, G. A. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.161273698 · Cited by 474 · see citing works

Gene expression analysis with the parametric bootstrap

van der Laan, M. J. (2001) · Biostatistics · doi:10.1093/biostatistics/2.4.445 · Cited by 96 · see citing works

Calculation of the minimum number of replicate spots required for detection of significant gene expression fold change in microarray experiments

Black, M. A., & Doerge, R. W. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.12.1609 · Cited by 75 · see citing works

Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments

Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829 · see citing works

Statistical significance for genomewide studies

Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692 · see citing works

A Direct Approach to False Discovery Rates

Storey, J. D. (2002) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00346 · Cited by 5,603 · see citing works

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 · see citing works

… and the Cross-Section of Expected Returns

Harvey, C. R., Liu, Y., & Zhu, H. (2016) · Review of Financial Studies · doi:10.1093/rfs/hhv059 · Cited by 2,119 · see citing works

The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores

Irizarry, R. A., Ladd-Acosta, C., Wen, B., Wu, Z., Montano, C., Onyango, P., Cui, H., Gabo, K., Rongione, M., Webster, M., et al. (2009) · Nature Genetics · doi:10.1038/ng.298 · Cited by 2,177 · see citing works

Microarray data analysis: from disarray to consolidation and consensus

Allison, D. B., Cui, X., Page, G. P., & Sabripour, M. (2006) · Nature Reviews Genetics · doi:10.1038/nrg1749 · Cited by 1,339 · see citing works

A Large-Scale Genetic Association Study Confirms IL12B and Leads to the Identification of IL23R as Psoriasis-Risk Genes

Cargill, M., Schrodi, S. J., Chang, M., Garcia, V. E., Brandon, R., Callis, K. P., Matsunami, N., Ardlie, K. G., Civello, D., Catanese, J. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/511051 · Cited by 1,086 · see citing works

How does multiple testing correction work?

Noble, W. S. (2009) · Nature Biotechnology · doi:10.1038/nbt1209-1135 · Cited by 772 · see citing works

Empirical Bayes methods and false discovery rates for microarrays

Efron, B., & Tibshirani, R. (2002) · Genetic Epidemiology · doi:10.1002/gepi.1124 · Cited by 684 · see citing works

Assigning Significance to Peptides Identified by Tandem Mass Spectrometry Using Decoy Databases

Käll, L., Storey, J. D., MacCoss, M. J., & Noble, W. S. (2008) · Journal of Proteome Research · doi:10.1021/pr700600n · Cited by 607 · see citing works

A survey on filter techniques for feature selection in gene expression microarray analysis

Lazar, C., Taminau, J., Meganck, S., Steenhoff, D., Coletta, A., Molter, C., de Schaetzen, V., Duque, R., Bersini, H., & Nowe, A. (2012) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2012.33 · Cited by 619 · see citing works

Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria

Pejaver, V., Byrne, A. B., Feng, B.-J., Pagel, K. A., Mooney, S. D., Karchin, R., O’Donnell-Luria, A., Harrison, S. M., Tavtigian, S. V., Greenblatt, M. S., et al. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.10.013 · Cited by 589 · see citing works

Rank–rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures

Plaisier, S. B., Taschereau, R., Wong, J. A., & Graeber, T. G. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq636 · Cited by 468 · see citing works

Correlation and Large-Scale Simultaneous Significance Testing

Efron, B. (2007) · Journal of the American Statistical Association · doi:10.1198/016214506000001211 · Cited by 405 · see citing works

Robustly detecting differential expression in RNA sequencing data using observation weights

Zhou, X., Lindsay, H., & Robinson, M. D. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku310 · Cited by 387 · see citing works

An exploration of aspects of Bayesian multiple testing

Scott, J. G., & Berger, J. O. (2006) · Journal of Statistical Planning and Inference · doi:10.1016/j.jspi.2005.08.031 · Cited by 330 · see citing works

Intensity-based hierarchical bayes method improves testing for differentially expressed genes in microarray experiments

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 · see citing works

MultipleTesting.com: A tool for life science researchers for multiple hypothesis testing correction

Menyhart, O., Weltz, B., & Győrffy, B. (2021) · PLOS ONE · doi:10.1371/journal.pone.0245824 · Cited by 216 · see citing works

Genome-wide pharmacogenomic study of neurocognition as an indicator of antipsychotic treatment response in schizophrenia

McClay, J. L., Adkins, D. E., Åberg, K., Bukszár, J., Khachane, A. N., Keefe, R. S. E., Perkins, D. O., McEvoy, J. P., Stroup, T. S., Vann, R. E., et al. (2011) · Neuropsychopharmacology · doi:10.1038/npp.2010.193 · Cited by 124 · see citing works

Comparative study of RNA-seq- and Microarray-derived coexpression networks in <i>Arabidopsis thaliana</i>

Giorgi, F. M., Del Fabbro, C., & Licausi, F. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt053 · Cited by 103 · see citing works

Integrative differential expression and gene set enrichment analysis using summary statistics for scRNA-seq studies

Ma, Y., Sun, S., Shang, X., Keller, E. T., Chen, M., & Zhou, X. (2020) · Nature Communications · doi:10.1038/s41467-020-15298-6 · Cited by 81 · see citing works

Paternal adverse childhood experiences: Associations with infant DNA methylation

Merrill, S. M., Moore, S. R., Gladish, N., Giesbrecht, G. F., Dewey, D., Konwar, C., MacIssac, J. L., Kobor, M. S., & Letourneau, N. L. (2021) · Developmental Psychobiology · doi:10.1002/dev.22174 · Cited by 42 · see citing works

An empirical Bayes model using a competition score for metabolite identification in gas chromatography mass spectrometry

Jeong, J., Shi, X., Zhang, X., Kim, S., & Shen, C. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-392 · Cited by 27 · see citing works

A Unified View of False Discovery Rate Control: Reconciliation of Bayesian and Frequentist ApproachesPreprint

Wen, X. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1803.05284 · Cited by 4 · see citing works

Comparing the frequentist and Bayesian periodic signal detection: rates of statistical mistakes and sensitivity to priors

Baluev, R. V. (2022) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stac762 · Cited by 7 · see citing works

Frequentist and Bayesian Hypothesis Testing: An Intuitive Guide for Urologists and Clinicians

Gaona, J. L., Sánchez, D., González, C., Gonzalez, F. A., Rueda, A., & Ortiz, S. (2022) · Revista Urología Colombiana / Colombian Urology Journal · doi:10.1055/s-0042-1756171

Bayesiant-tests for correlations and partial correlations

Wang, M., Chen, F., Lu, T., & Dong, J. (2019) · Journal of Applied Statistics · doi:10.1080/02664763.2019.1695760 · Cited by 1 · see citing works

Simultaneous Bayesian-frequentist sequential testing of nested hypotheses

Berger, J. O. (1999) · Biometrika · doi:10.1093/biomet/86.1.79 · Cited by 32 · see citing works