ProbCD: enrichment analysis accounting for categorization uncertainty
Open Access
- 12 October 2007
- journal article
- Published by Springer Nature in BMC Bioinformatics
- Vol. 8 (1) , 383
- https://doi.org/10.1186/1471-2105-8-383
Abstract
As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test.Keywords
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This publication has 23 references indexed in Scilit:
- Estimating the annotation error rate of curated GO database sequence annotationsBMC Bioinformatics, 2007
- Analyzing gene expression data in terms of gene sets: methodological issuesBioinformatics, 2007
- Enrichment or depletion of a GO category within a class of genes: which test?Bioinformatics, 2006
- Extensions to gene set enrichmentBioinformatics, 2006
- Functional Interpretation of Microarray ExperimentsOMICS: A Journal of Integrative Biology, 2006
- Protein classification using probabilistic chain graphs and the Gene Ontology structureBioinformatics, 2006
- Protein Molecular Function Prediction by Bayesian PhylogenomicsPLoS Computational Biology, 2005
- BiNGO: a Cytoscape plugin to assess overrepresentation of Gene Ontology categories in Biological NetworksBioinformatics, 2005
- Genome-Scale Gene Function Prediction Using Multiple Sources of High-Throughput Data in Yeast Saccharomyces cerevisiaeOMICS: A Journal of Integrative Biology, 2004
- On the Interpretation of χ 2 from Contingency Tables, and the Calculation of PJournal of the Royal Statistical Society, 1922