SynthesisBMC bioinformatics2007
A latent variable approach for meta-analysis of gene expression data from multiple microarray experiments.
Synthesis in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 7 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
33 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Transforming evidence synthesis: A systematic review of the evolution of automated meta-analysis in the age of AI.Research synthesis methods · 2026Pooled it
- Meta-Analysis Based on Nonconvex Regularization.Scientific reports · 2020Pooled it
- Meta-analysis of gene expression in relapsed childhood B-acute lymphoblastic leukemia.BMC cancer · 2017Pooled it
- Pooled it
- Pooled it
- A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide.Bioinformatics (Oxford, England) · 2009Pooled it
- Disease signatures are robust across tissues and experiments.Molecular systems biology · 2009Pooled it
- Consensus Transcriptional Landscape of Human End-Stage Heart Failure.Journal of the American Heart Association · 2021Review
- Comparative transcriptome analysis of Parkinson's disease and Hutchinson-Gilford progeria syndrome reveals shared susceptible cellular network processes.BMC medical genomics · 2020Article
- Available Software for Meta-analyses of Genome-wide Expression Studies.Current genomics · 2019Review
- Global analysis of gene expression in maize leaves treated with low temperature. II. Combined effect of severe cold (8 °C) and circadian rhythm.Plant molecular biology · 2017Article
- Quantitative reproducibility analysis for identifying reproducible targets from high-throughput experiments.BMC systems biology · 2017Article
- Identification of differentially-expressed genes between early-stage adenocarcinoma and squamous cell carcinoma lung cancer using meta-analysis methods.Oncology letters · 2017Article
- DANUBE: Data-driven meta-ANalysis using UnBiased Empirical distributions-applied to biological pathway analysis.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2017Article
- A novel bi-level meta-analysis approach: applied to biological pathway analysis.Bioinformatics (Oxford, England) · 2016Article
- ExAtlas: An interactive online tool for meta-analysis of gene expression data.Journal of bioinformatics and computational biology · 2015Article
- Imputation of TruncatedThe annals of applied statistics · 2014Article
- Article
- Pathprinting: An integrative approach to understand the functional basis of disease.Genome medicine · 2013Article
- Integrative prescreening in analysis of multiple cancer genomic studies.BMC bioinformatics · 2012Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWith the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies.
resultsIn this article, we describe a general probabilistic framework for combining high-throughput genomic data from several related microarray experiments using mixture models. A key feature of the model is the use of latent variables that represent quantities that can be combined across diverse platforms. We consider two methods for estimation of an index termed the probability of expression (POE). The first, reported in previous work by the authors, involves Markov Chain Monte Carlo (MCMC) techniques. The second method is a faster algorithm based on the expectation-maximization (EM) algorithm. The methods are illustrated with application to a meta-analysis of datasets for metastatic cancer.
conclusionThe statistical methods described in the paper are available as an R package, metaArray 1.8.1, which is at Bioconductor, whose URL is http://www.bioconductor.org/.
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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.