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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  4 years and 2 months ago 2631 main
conda 554.3 kB | noarch/r-leapp-1.2-r40h3342da4_3.tar.bz2  4 years and 4 months ago 296 main
conda 554.1 kB | noarch/r-leapp-1.2-r40h6115d3f_2.tar.bz2  5 years and 3 months ago 326 main
conda 553.4 kB | noarch/r-leapp-1.2-r36h6115d3f_1.tar.bz2  5 years and 11 months ago 370 main
conda 551.5 kB | linux-64/r-leapp-1.2-r351h6115d3f_0.tar.bz2  6 years and 8 months ago 506 main cf201901
conda 552.0 kB | osx-64/r-leapp-1.2-r351h6115d3f_0.tar.bz2  6 years and 8 months ago 2092 main cf201901

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