Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations
نویسندگان
چکیده
منابع مشابه
Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations
Enrichment analysis of gene sets is a popular approach that provides a functional interpretation of genome-wide expression data. Existing tests are affected by inter-gene correlations, resulting in a high Type I error. The most widely used test, Gene Set Enrichment Analysis, relies on computationally intensive permutations of sample labels to generate a null distribution that preserves gene-gen...
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Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA) introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estima...
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Gene set enrichment analysis (GSEA) is a statistical method to determine if predefined sets of genes are differentially expressed in different phenotypes. Predefined gene sets may be genes in a known metabolic pathway, located in the same cytogenetic band, sharing the same Gene Ontology category, or any user-defined set. In microarray experiments where no single gene shows statistically signifi...
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MOTIVATION Group-wise pattern analysis of genes, known as gene-set analysis (GSA), addresses the differential expression pattern of biologically pre-defined gene sets. GSA exhibits high statistical power and has revealed many novel biological processes associated with specific phenotypes. In most cases, however, GSA relies on the invalid assumption that the members of each gene set are sampled ...
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ژورنال
عنوان ژورنال: Nucleic Acids Research
سال: 2013
ISSN: 0305-1048,1362-4962
DOI: 10.1093/nar/gkt660