ArticleBMC bioinformatics2009
An improved empirical bayes approach to estimating differential gene expression in microarray time-course data: BETR (Bayesian Estimation of Temporal Regulation).
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled it.
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Who cites it
59 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
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- Information sharing in high-dimensional gene expression data for improved parameter estimation in concentration-response modelling.PloS one · 2023Article
- Benchmarking tools for detecting longitudinal differential expression in proteomics data allows establishing a robust reproducibility optimization regression approach.Nature communications · 2022Article
- Rewiring of the Liver Transcriptome across Multiple Time-Scales Is Associated with the Weight Loss-Independent Resolution of NAFLD Following RYGB.Metabolites · 2022Article
- Abrogation of Rb Tumor Suppression Initiates GBM in Differentiated Astrocytes by Driving a Progenitor Cell Program.Frontiers in oncology · 2022Article
- Long-Lasting Defence Priming by β-Aminobutyric Acid in Tomato Is Marked by Genome-Wide Changes in DNA Methylation.Frontiers in plant science · 2022Article
- Exosomal MicroRNAs as Potential Biomarkers of Hepatic Injury and Kidney Disease in Glycogen Storage Disease Type Ia Patients.International journal of molecular sciences · 2021Article
- Tissue-Specific Metabolic Reprogramming during Wound-Induced Organ Formation in Tomato Hypocotyl Explants.International journal of molecular sciences · 2021Article
- Circulating exosomal microRNAs as potential biomarkers of hepatic injury and inflammation in a murine model of glycogen storage disease type 1a.Disease models & mechanisms · 2020Article
- Understanding the Molecular Mechanisms of Asthma through Transcriptomics.Allergy, asthma & immunology research · 2020Review
- A Longitudinal Model of Human Neuronal Differentiation for Functional Investigation of Schizophrenia Polygenic Risk.Biological psychiatry · 2019Article
- Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance.Genome medicine · 2018Article
- Wounding Triggers Callus Formation via Dynamic Hormonal and Transcriptional Changes.Plant physiology · 2017Article
- Petri Net computational modelling of Langerhans cell Interferon Regulatory Factor Network predicts their role in T cell activation.Scientific reports · 2017Article
- Identification of temporal genes involved in the mechanisms of spinal cord injury.Spinal cord · 2017Article
- TTCA: an R package for the identification of differentially expressed genes in time course microarray data.BMC bioinformatics · 2017Article
- DynOmics to identify delays and co-expression patterns across time course experiments.Scientific reports · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundMicroarray gene expression time-course experiments provide the opportunity to observe the evolution of transcriptional programs that cells use to respond to internal and external stimuli. Most commonly used methods for identifying differentially expressed genes treat each time point as independent and ignore important correlations, including those within samples and between sampling times. Therefore they do not make full use of the information intrinsic to the data, leading to a loss of power.
resultsWe present a flexible random-effects model that takes such correlations into account, improving our ability to detect genes that have sustained differential expression over more than one time point. By modeling the joint distribution of the samples that have been profiled across all time points, we gain sensitivity compared to a marginal analysis that examines each time point in isolation. We assign each gene a probability of differential expression using an empirical Bayes approach that reduces the effective number of parameters to be estimated.
conclusionsBased on results from theory, simulated data, and application to the genomic data presented here, we show that BETR has increased power to detect subtle differential expression in time-series data. The open-source R package betr is available through Bioconductor. BETR has also been incorporated in the freely-available, open-source MeV software tool available from http://www.tm4.org/mev.html.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.