ArticleGenome biology2022
Comparison of confound adjustment methods in the construction of gene co-expression networks.
Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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
7 citing papers in PubMed.
- Response to commentary on 'CorrAdjust unveils biologically relevant transcriptomic correlations by efficiently eliminating hidden confounders'.Nucleic acids research · 2026Article
- Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networks.Genome research · 2025Article
- CorrAdjust unveils biologically relevant transcriptomic correlations by efficiently eliminating hidden confounders.Nucleic acids research · 2025Article
- GWAS-based population genetic analysis identifies bZIP29 as a heterotic gene in maize.Plant communications · 2025Article
- Decoding the transcriptomic signatures of psychological trauma in human cortex and amygdala.bioRxiv : the preprint server for biology · 2024Article
- Transcriptome data are insufficient to control false discoveries in regulatory network inference.Cell systems · 2024Article
- Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings.Translational psychiatry · 2023Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Adjustment for confounding sources of expression variation is an important preprocessing step in large gene expression studies, but the effect of confound adjustment on co-expression network analysis has not been well-characterized. Here, we demonstrate that the choice of confound adjustment method can have a considerable effect on the architecture of the resulting co-expression network. We compare standard and alternative confound adjustment methods and provide recommendations for their use in the construction of gene co-expression networks from bulk tissue RNA-seq datasets.
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Registered trials
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