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These functions take a gene expression value matrix, a primary covariate vector, an additional known covariates matrix. A two stage analysis is applied to counter the effects of latent variables on the rankings of hypotheses. The estimation and adjustment of latent effects are proposed by Sun, Zhang and Owen (2011). "leapp" is developed in the context of microarray experiments, but may be used as a general tool for high throughput data sets where dependence may be involved.

Type Size Name Uploaded Downloads Labels
conda 554.4 kB | noarch/r-leapp-1.2-r41h3342da4_4.tar.bz2  3 years and 5 months ago 2330 main
conda 554.3 kB | noarch/r-leapp-1.2-r40h3342da4_3.tar.bz2  3 years and 7 months ago 232 main
conda 554.1 kB | noarch/r-leapp-1.2-r40h6115d3f_2.tar.bz2  4 years and 6 months ago 261 main
conda 553.4 kB | noarch/r-leapp-1.2-r36h6115d3f_1.tar.bz2  5 years and 2 months ago 303 main
conda 551.5 kB | linux-64/r-leapp-1.2-r351h6115d3f_0.tar.bz2  5 years and 11 months ago 432 main cf201901
conda 552.0 kB | osx-64/r-leapp-1.2-r351h6115d3f_0.tar.bz2  5 years and 11 months ago 2073 main cf201901

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