RBM_F {RBM} | R Documentation |
Use A Resampling-Based Empirical Bayes Approach to Assess Differential Expression in Two-Color Microarrays and RNA-Seq data sets for designs with more than two groups.
RBM_F(aData, vec_trt, aContrast, repetition, alpha)
aData |
The input data set with rows and columns denoting features and samples, respectively |
vec_trt |
A vector for group notation such as 1s denote treatment group and 0s denote control group |
aContrast |
A vector for contrast. For example: if we want to compare group 1 with group 0, group 2 with group 1, and group 2 with group 0, then the contrast vector will be ("X1-X0", "X2"-"X1", "X2-X0") |
repetition |
The number of resamplings used in the analysis. You could use 1000 or higher number |
alpha |
The signifiance level |
Combine resampling with empirical Bayes approach for Microarrays and RNA-Seq data analysis.
RBM_F produces a named list with the following components:
ordfit_t |
orignal t statistics |
ordfit_pvalue |
original p-values from lmFit and eBayes |
ordfit_beta0 |
estimated mean for the control group |
ordfit_beta1 |
estimated mean difference between treatment and control group |
permutation_p |
calculated p-values from permutation method based on resampled test statistics |
bootstrap_p |
calculated p-values from bootstrap method based on resampled test statistics |
Dongmei Li and Chin-Yuan Liang
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
function defined in this package.
The limma and marray packages.
normdata_F <- matrix(rnorm(200*9, 0, 2), 200, 9) mydesign_new <- 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_new, aContrast, 100, 0.05) unifdata_F <- matrix(runif(200*18, 0.15, 0.98), 200, 18) mydesign2_new <- 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_new, aContrast, 100, 0.05)