Nonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments

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dc.contributor.authorGao, Xin
dc.contributor.authorSong, Peter XK
dc.date.accessioned2007-10-10T13:40:13Z
dc.date.available2007-10-10T13:40:13Z
dc.date.issued2005-07-21
dc.description.abstractBackground Numerous nonparametric approaches have been proposed in literature to detect differential gene expression in the setting of two user-defined groups. However, there is a lack of nonparametric procedures to analyze microarray data with multiple factors attributing to the gene expression. Furthermore, incorporating interaction effects in the analysis of microarray data has long been of great interest to biological scientists, little of which has been investigated in the nonparametric framework. Results In this paper, we propose a set of nonparametric tests to detect treatment effects, clinical covariate effects, and interaction effects for multifactorial microarray data. When the distribution of expression data is skewed or heavy-tailed, the rank tests are substantially more powerful than the competing parametric F tests. On the other hand, in the case of light or medium-tailed distributions, the rank tests appear to be marginally less powerful than the parametric competitors. Conclusion The proposed rank tests enable us to detect differential gene expression and establish interaction effects for microarray data with various non-normally distributed expression measurements across genome. In the presence of outliers, they are advantageous alternative approaches to the existing parametric F tests due to the robustness feature.
dc.identifier.citationGao, X. and Song, P. (2005). Nonparametric Tests for Differential Gene Expression and Interaction Effects for Multi-factorial Microarray Experiments, BMC Bioinformtics, Vol. 6:186.
dc.identifier.issn1471-2105
dc.identifier.urihttp://hdl.handle.net/10315/1159
dc.identifier.urihttps://doi.org/10.1186/1471-2105-6-186
dc.language.isoen
dc.publisherBioMed Central
dc.subjectNonparametric tests
dc.subjectDifferential gene expression
dc.subjectInteraction effects
dc.subjectMulti-factorial experiments
dc.subjectMicroarray data
dc.titleNonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments
dc.typeArticle

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