RANDOM-SET METHODS IDENTIFY DISTINCT ASPECTS OF THE ENRICHMENT SIGNAL IN GENE-SET ANALYSIS

Simple item page
dc.contributor.authorNewton, Michael A.
dc.contributor.authorQuintana, Fernando A.
dc.contributor.authorDen Boon, Johan A.
dc.contributor.authorSengupta, Srikumar
dc.contributor.authorAhlquist, Paui
dc.date.accessioned2024-01-10T12:41:57Z
dc.date.available2024-01-10T12:41:57Z
dc.date.issued2007
dc.description.abstractA prespecified set of genes may be enriched, to varying degrees, for genes that have altered expression levels relative to two or more states of a cell. Knowing the enrichment of gene sets defined by functional categories. such as gene ontology (GO) annotations, is valuable for analyzing the biological signals in microarray expression data. A common approach to measuring enrichment is by cross-classifying genes according to membership in a functional category and membership oil a selected list of significantly altered genes. A small Fisher's exact test P-value, for example, in this 2 x 2 table is indicative of enrichment. Other category analysis methods retain the quantitative gene-level scores and measure significance by referring a category-level statistic to a permutation distribution associated with the original differential expression problem. We describe a class of random-set scoring methods that measure distinct components of the enrichment signal. The class includes Fisher's test based on selected genes and also tests that average gene-level evidence across the category. Averaging and selection methods are compared empirically using Affymetrix data on expression in nasopharyngeal cancer tissue, and theoretically using a location model of differential, expression. We find that each method has a domain of superiority in the state space of enrichment problems, and that both methods have benefits in practice. Our analysis also addresses two problems related to multiple-category inference, namely, that equally enriched categories are not detected with equal probability if they are of different sizes, and also that there is dependence among category statistics owing to shared genes. Random-set enrichment calculations do not require Monte Carlo for implementation. They are made available in the R package allez.
dc.description.funderNational Cancer Institute
dc.description.funderFONDECYT
dc.fechaingreso.objetodigital2024-05-15
dc.format.extent22 páginas
dc.fuente.origenWOS
dc.identifier.doi10.1214/07-AOAS104
dc.identifier.issn1932-6157
dc.identifier.urihttps://doi.org/10.1214/07-AOAS104
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/77467
dc.identifier.wosidWOS:000261050400005
dc.information.autorucMatemática;Quintana F;S/I;100343
dc.issue.numero1
dc.language.isoen
dc.nota.accesocontenido completo
dc.pagina.final106
dc.pagina.inicio85
dc.publisherINST MATHEMATICAL STATISTICS
dc.revistaANNALS OF APPLIED STATISTICS
dc.rightsacceso abierto
dc.subjectConditional testing
dc.subjectgene ontology
dc.subjectgene set enrichment analysis
dc.subjecthost-virus association in nasopharyngeal carcinoma
dc.subjectselection versus average evidence
dc.subjectsignificance analysis of function and expression
dc.subjectMICROARRAY DATA
dc.subjectEXPRESSION
dc.subjectONTOLOGY
dc.subjectTOOL
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleRANDOM-SET METHODS IDENTIFY DISTINCT ASPECTS OF THE ENRICHMENT SIGNAL IN GENE-SET ANALYSIS
dc.typeartículo
dc.volumen1
sipa.codpersvinculados100343
sipa.indexWOS
sipa.indexScopus
sipa.trazabilidadCarga SIPA;09-01-2024
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
The Annals of Applied Statistics - 2007 - Random-set methods identify distinct aspects of the enrichment signal in gene-set analysis.pdf
Size:
3.36 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Artículos de revistas