ArticlePloS one2010
Multidimensional gene set analysis of genomic data.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 6 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
56 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- A comprehensive transcriptional reference for severity and progression in spinal cord injury reveals novel translational biomarker genes.Journal of translational medicine · 2025Pooled it
- The impact of sex on gene expression in the brain of schizophrenic patients: a systematic review and meta-analysis of transcriptomic studies.Biology of sex differences · 2024Pooled it
- The role of microRNAs in understanding sex-based differences in Alzheimer's disease.Biology of sex differences · 2024Pooled it
- Hepatic steatosis and steatohepatitis: a functional meta-analysis of sex-based differences in transcriptomic studies.Biology of sex differences · 2021Pooled it
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- iBBiG: iterative binary bi-clustering of gene sets.Bioinformatics (Oxford, England) · 2012Pooled it
- Integrated lipidome and miRNome analyses reveal sex-based differences in circulating extracellular vesicles of alcohol use disorder patients.Cell biology and toxicology · 2026Article
- Meta-analysis of the melanoma miRNome identifies consensus signatures of progression and prognosis regulating metabolic plasticity and stress resistance.bioRxiv : the preprint server for biology · 2026Article
- Glymphatic dysfunction and neuroinflammation in FXTAS: evidence from DTI-ALPS and gene expression analysis.Frontiers in molecular neuroscience · 2026Article
- MetaFun: unveiling sex-based differences in multiple transcriptomic studies through comprehensive functional meta-analysis.Biology of sex differences · 2024Article
- Novel insight into the lipid network of plasma extracellular vesicles reveal sex-based differences in the lipidomic profile of alcohol use disorder patients.Biology of sex differences · 2024Article
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- Lipidomic landscape of circulating extracellular vesicles isolated from adolescents exposed to ethanol intoxication: a sex difference study.Biology of sex differences · 2023Article
- Ptpn1 deletion protects oval cells against lipoapoptosis by favoring lipid droplet formation and dynamics.Cell death and differentiation · 2022Article
- Bioenergetic and Autophagic Characterization of Skin Fibroblasts fromAntioxidants (Basel, Switzerland) · 2022Article
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- Multi-omic analysis unveils biological pathways in peripheral immune system associated to minimal hepatic encephalopathy appearance in cirrhotic patients.Scientific reports · 2021Article
- Review
- Exploring sunflower responses to Sclerotinia head rot at early stages of infection using RNA-seq analysis.Scientific reports · 2020Article
- Transcriptional signature of resting-memory CD4 T cells differentiates spontaneous from treatment-induced HIV control.Journal of molecular medicine (Berlin, Germany) · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding the functional implications of changes in gene expression, mutations, etc., is the aim of most genomic experiments. To achieve this, several functional profiling methods have been proposed. Such methods study the behaviour of different gene modules (e.g. gene ontology terms) in response to one particular variable (e.g. differential gene expression). In spite to the wealth of information provided by functional profiling methods, a common limitation to all of them is their inherent unidimensional nature. In order to overcome this restriction we present a multidimensional logistic model that allows studying the relationship of gene modules with different genome-scale measurements (e.g. differential expression, genotyping association, methylation, copy number alterations, heterozygosity, etc.) simultaneously. Moreover, the relationship of such functional modules with the interactions among the variables can also be studied, which produces novel results impossible to be derived from the conventional unidimensional functional profiling methods. We report sound results of gene sets associations that remained undetected by the conventional one-dimensional gene set analysis in several examples. Our findings demonstrate the potential of the proposed approach for the discovery of new cell functionalities with complex dependences on more than one variable.
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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.