Identifying differentially expressed genes using false discovery rate controlling procedures

By Anat Reiner, D. Yekutieli, Yoav Benjamini. Bioinform., 2003

1,860 citations recorded by the source corpus.

Subfields: Molecular Biology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/130709f64a0d1762af9da63cb97975fca198311b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

In Statistics and Probability

Citations in the corpus

Control of the false discovery rate under dependence using the bootstrap and subsampling (2008, methodology): “The bootstrap data are generated using the circular block bootstrap of Politis and Romano (1992), based on B = 5, 000 repetitions.”
Correlation and Large-Scale Simultaneous Significance Testing (2007, background): “Fdr(x) is an empirical Bayes estimate of the a posteriori probability that case i is null given zi ≥ x, Storey (2002), Efron and Tibshirani (2002), amounting to a version of Storey’s “q-value”.”
Asymptotic optimality of the Westfall--Young permutation procedure for multiple testing under dependence (2011, background): “[27] discuss the gain of resampling in terms of power, although their focus is mainly on FDR controlling methods.”
Procedures for numerical analysis of circadian rhythms (2007, methodology): “Its application specifically to the analysis of microarray data has been suggested by statisticians (Reiner et al. 2003; Storey & Tibshirani 2003; Taylor et al. 2005), and at least one circadian microarray study has utilized it (Ptitsyn et al. 2006).”
Oxygen sensing in plants is mediated by an N-end rule pathway for protein destabilization (2011, methodology): “Differential gene expression analysis was carried out using limm”
Control of the mean number of false discoveries, Bonferroni and stability of multiple testing (2007, background): “The quest for less conservative MTPs has resulted in many new concepts of error rate, such as the false discovery rate (FDR) [Benjamini and Hochberg (1995), Yekutieli and Benjamini (1999), Benjamini and Hochberg (2000), Reiner, Yekutieli and Benjamini (2003) ] and its local version [Efron (2003)], ”
A Central Regulatory System Largely Controls Transcriptional Activation and Repression Responses to Phosphate Starvation in Arabidopsis (2010, methodology): “P-values were corrected for multiple-testing using the Benjamini-Hochberg method (False Discovery Rate) [67].”
Transcriptional Profiling of the Human Monocyte-to-Macrophage Differentiation and Polarization: New Molecules and Patterns of Gene Expression1 (2006, methodology): “Gene expression differences were assessed by means of Student’s t test, with false discovery rate correction for multiple testing (23) (R Bioconductor).”
Fundamentals of cDNA microarray data analysis. (2003, background): “Therefore it might be more practical to control the false discovery rate (FDR) [25], the expected proportion of false positives among the number of rejected hypotheses.”
FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes (2004, methodology): “In addition, as the number of genes with GO annotations increases in the next few years, functional genomics will benefit from the use of applications, such as FatiGO, based on GO terms.”
On control of the false discovery rate under no assumption of dependency (2008, methodology): “The FDR has been extensively used in many applications such as microarray data analysis (Reiner et al., 2003), clinical trials (Mehrotra and Heyse, 2004), model selection (Abramovich et al., 2006), and educational evaluation (Williams et al., 1999).”
Analytical Methods in Untargeted Metabolomics: State of the Art in 2015 (2015, methodology): “Most of these methods have been extensively used for the analysis of gene-expression microarray data, where thousands of genes are tested in parallel (Reiner et al., 2003; Jung, 2005; Xie et al., 2005).”
Beyond Bonferroni: less conservative analyses for conservation genetics (2006, methodology): “FDR procedures have been successfully used in situationswithvery largenumbersofpairwise tests such as microarray gene expression (Reiner et al. 2003) and neuroimaging (Genovese et al.”
limma: Linear Models for Microarray Data (2005, background): “Benjamini and Hochberg’s control of the false discovery rate assumes independence between genes, although Reiner et al [7] have argued that it works for many forms of dependence as well.”
Statistical strategies for avoiding false discoveries in metabolomics and related experiments (2007, methodology): “…of course, a characteristic of omics studies that has long been highlighted following the development of microarrays for transcriptomics (e.g. (Benjamini and Hochberg, 1995; Efron and Tibshirani, 2002; Storey, 2002; Storey and Tibshirani , 2003; Reiner et al., 2003; Jung, 2005; Xie et al., 2005)).”
A multivariate empirical Bayes statistic for replicated microarray time course data (2006, methodology): “The most widely used method for identifying temporally changing genes in replicated microarray experiments is to carry out multiple pairwise comparisons across times, using statistics developed for comparing two independent samples, [2, 6, 13, 19, 20, 23, 24, 33].”
Estimating the proportion of true null hypotheses, with application to DNA microarray data (2005, methodology): “Here, % is Schweder and Spjøtvoll’s (1982) estimator with Storey’s (2002b) bootstrap choice of from Section 4.”