Cited by 330Gene expression and cancer classificationBioinformatics and Genomic NetworksGenomics and Phylogenetic Studies

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Dream: powerful differential expression analysis for repeated measures designs

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Hoffman, Gabriel E, Roussos, Panos·2021·Bioinformatics

DOI 10.1093/bioinformatics/btaa687PMC PMC8055218

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Abstract

Summary: Large-scale transcriptome studies with multiple samples per individual are widely used to study disease biology. Yet, current methods for differential expression are inadequate for cross-individual testing for these repeated measures designs. Most problematic, we observe across multiple datasets that current methods can give reproducible false-positive findings that are driven by genetic regulation of gene expression, yet are unrelated to the trait of interest. Here, we introduce a statistical software package, dream, that increases power, controls the false positive rate, enables multiple types of hypothesis tests, and integrates with standard workflows. In 12 analyses in 6 independent datasets, dream yields biological insight not found with existing software while addressing the issue of reproducible false-positive findings. Availability and implementation: Dream is available within the variancePartition Bioconductor package at http://bioconductor.org/packages/variancePartition. Contact: gabriel.hoffman@mssm.edu Supplementary information: Supplementary data are available at Bioinformatics online.

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Authors: Hoffman, G. E., & Roussos, P.
Affiliations: Icahn School of Medicine at Mount Sinai (US)
James J. Peters VA Medical Center (US)
Corresponding author: Hoffman, Gabriel E
ORCID: Hoffman, Gabriel E
Roussos, Panos
Venue: Bioinformatics
Publisher: Oxford University Press (OUP)
Published: 2020-07-30
Volume: 37
Issue: 2
Pages: 192-201
ISSN: 1367-4803 (ISSN-L)
1367-4811
DOI: 10.1093/bioinformatics/btaa687
PMC: PMC8055218
OpenAlex: W3046454618
Cited by: 319
References: 74
Citations by year: 2026: 79 · 2025: 62 · 2024: 69 · 2023: 44 · 2022: 34 · 2021: 27 · 2020: 3
FWCI: 9.17
Type: journal article
Language: en
Open access: green
doi.org
Licence: cc-by-nc-nd
academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
Locations: Bioinformatics (publishedVersion)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: NIMH (U01MH116442, R01MH109677, R01MH109897, R01MH110921)
NIA (R01AG050986)
Veterans Affairs merit (BX002395)
NARSAD Young Investigator Award (26313)
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: differential gene expression, repeated measures designs, gene expression profiling, false positive rate control, genetic regulation of gene expression, statistical software, reproducibility
MeSH terms: Gene Expression Regulation, Software, Gene Expression Profiling, Transcriptome

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