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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 556.7 kB | noarch/r-leapp-1.3-r43h3342da4_2.tar.bz2  1 year and 5 months ago 1071 main
conda 555.9 kB | noarch/r-leapp-1.3-r42h3342da4_1.tar.bz2  2 years and 1 month ago 648 main
conda 555.4 kB | noarch/r-leapp-1.3-r41h3342da4_0.tar.bz2  2 years and 5 months ago 385 main
conda 554.4 kB | noarch/r-leapp-1.2-r41h3342da4_4.tar.bz2  3 years and 6 months ago 2395 main
conda 554.3 kB | noarch/r-leapp-1.2-r40h3342da4_3.tar.bz2  3 years and 8 months ago 237 main
conda 554.1 kB | noarch/r-leapp-1.2-r40h6115d3f_2.tar.bz2  4 years and 7 months ago 266 main
conda 553.4 kB | noarch/r-leapp-1.2-r36h6115d3f_1.tar.bz2  5 years and 3 months ago 309 main
conda 551.5 kB | linux-64/r-leapp-1.2-r351h6115d3f_0.tar.bz2  6 years and 18 days ago 440 main cf201901
conda 552.0 kB | osx-64/r-leapp-1.2-r351h6115d3f_0.tar.bz2  6 years and 18 days ago 2075 main cf201901

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