ArticleBMC bioinformatics2009
A methodology for the analysis of differential coexpression across the human lifespan.
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 13 papers.
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Who cites it
13 citing papers in PubMed.
- Analyzing Co-expression Networks with Network Skeleton Extraction.Research square · 2026Article
- Gene function predicts divergence across molecular levels.bioRxiv : the preprint server for biology · 2026Article
- Identification of differentially expressed genes in small and non-small cell lung cancer based on meta-analysis of mRNA.Heliyon · 2019Article
- Differential coexpression in human tissues and the confounding effect of mean expression levels.Bioinformatics (Oxford, England) · 2019Article
- Predicting age from the transcriptome of human dermal fibroblasts.Genome biology · 2018Article
- MultiDCoX: Multi-factor analysis of differential co-expression.BMC bioinformatics · 2017Article
- The Detection of Metabolite-Mediated Gene Module Co-Expression Using Multivariate Linear Models.PloS one · 2016Article
- Pitfalls in the application of gene-set analysis to genetics studies.Trends in genetics : TIG · 2014Article
- Feline degenerative joint disease: a genomic and proteomic approach.Journal of feline medicine and surgery · 2013Article
- Current challenges and future potential of tomato breeding using omics approaches.Breeding science · 2013Article
- Exploring tomato gene functions based on coexpression modules using graph clustering and differential coexpression approaches.Plant physiology · 2012Article
- Identification of pathway deregulation--gene expression based analysis of consistent signal transduction.PloS one · 2012Article
- Gene set analysis exploiting the topology of a pathway.BMC systems biology · 2010Article
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2 authors.
Funding
Abstract
backgroundDifferential coexpression is a change in coexpression between genes that may reflect 'rewiring' of transcriptional networks. It has previously been hypothesized that such changes might be occurring over time in the lifespan of an organism. While both coexpression and differential expression of genes have been previously studied in life stage change or aging, differential coexpression has not. Generalizing differential coexpression analysis to many time points presents a methodological challenge. Here we introduce a method for analyzing changes in coexpression across multiple ordered groups (e.g., over time) and extensively test its validity and usefulness.
resultsOur method is based on the use of the Haar basis set to efficiently represent changes in coexpression at multiple time scales, and thus represents a principled and generalizable extension of the idea of differential coexpression to life stage data. We used published microarray studies categorized by age to test the methodology. We validated the methodology by testing our ability to reconstruct Gene Ontology (GO) categories using our measure of differential coexpression and compared this result to using coexpression alone. Our method allows significant improvement in characterizing these groups of genes. Further, we examine the statistical properties of our measure of differential coexpression and establish that the results are significant both statistically and by an improvement in semantic similarity. In addition, we found that our method finds more significant changes in gene relationships compared to several other methods of expressing temporal relationships between genes, such as coexpression over time.
conclusionDifferential coexpression over age generates significant and biologically relevant information about the genes producing it. Our Haar basis methodology for determining age-related differential coexpression performs better than other tested methods. The Haar basis set also lends itself to ready interpretation in terms of both evolutionary and physiological mechanisms of aging and can be seen as a natural generalization of two-category differential coexpression. CONTACT: paul@bioinformatics.ubc.ca.
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