RBM-package {RBM} | R Documentation |
Use A Resampling-Based Empirical Bayes Approach to Assesse Differential Expression or Identifying differntially methylated loci in Two-Color Microarrays and RNA-Seq data sets. Significant features selected through RBM_T or RBM_F functions could be further used as input for pathway analysis or experimental vilidations.
Package: | RBM |
Type: | Package |
Version: | 0.99.0 |
Date: | 2014-10-05 |
Depends: | R (>= 3.0.0), limma, marray |
License: | GPL (>= 2) |
Dongmei Li and Chin-Yuan Liang Maintainer: Dongmei Li <dongmeiliur@gmail.com> and Chin-Yuan Liang <liang.tony@gmail.com>
Li D, Le Pape MA, Parikh NI, Chen WX, Dye TD (2013) Assessing Differential Expression in Two-Color Microarrays: A Resampling-Based Empirical Bayes Approach. PLoS ONE 8(11): e80099. doi: 10.1371/journal.pone.0080099
The RBM_T
and RBM_F
functions defined in this package.
The limma and marray packages.
normal_data <- matrix(rnorm(200*6), 200, 6) mydesign <- c(0,0,0,1,1,1) norm_result <- RBM_T(normal_data,mydesign,50,0.05) unif_data <- matrix(runif(200*7, 0.10, 0.95), 200, 7) mydesign2 <- c(0,0,0, 1,1,1,1) unif_result <- RBM_T(unif_data,mydesign2,100,0.05) normdata_F <- matrix(rnorm(200*9, 0, 2), 200, 9) mydesign_F <- c(0, 0, 0, 1, 1, 1, 2, 2, 2) aContrast <- c("X1-X0", "X2-X1", "X2-X0") normresult_F <- RBM_F(normdata_F, mydesign_F, aContrast, 100, 0.05) unifdata_F <- matrix(runif(200*18, 0.15, 0.98), 200, 18) mydesign2_F <- c(rep(0, 6), rep(1, 6), rep(2, 6)) aContrast <- c("X1-X0", "X2-X1", "X2-X0") unifresult_F <- RBM_F(unifdata_F, mydesign2_F, aContrast, 100, 0.05)