basicPLM {oligo} | R Documentation |
Simplified interface to PLM.
basicPLM(pmMat, pnVec, normalize = TRUE, background = TRUE, transfo = log2, method = c('plm', 'plmr', 'plmrr', 'plmrc'), verbose = TRUE)
pmMat |
Matrix of intensities to be processed. |
pnVec |
Probeset names |
normalize |
Logical flag: normalize? |
background |
Logical flag: background adjustment? |
transfo |
function: function to be used for data transformation prior to summarization. |
method |
Name of the method to be used for normalization. 'plm' is the usual PLM model; 'plmr' is the (row and column) robust version of PLM; 'plmrr' is the row-robust version of PLM; 'plmrc' is the column-robust version of PLM. |
verbose |
Logical flag: verbose. |
A list with the following components:
Estimates |
A (length(pnVec) x ncol(pmMat)) matrix with probeset summaries. |
StdErrors |
A (length(pnVec) x ncol(pmMat)) matrix with standard errors of 'Estimates'. |
Residuals |
A (nrow(pmMat) x ncol(pmMat)) matrix of residuals. |
Currently, only RMA-bg-correction and quantile normalization are allowed.
Benilton Carvalho
rcModelPLM
,
rcModelPLMr
,
rcModelPLMrr
,
rcModelPLMrc
,
basicRMA
set.seed(1) pms <- 2^matrix(rnorm(1000), nc=20) colnames(pms) <- paste("sample", 1:20, sep="") pns <- rep(letters[1:10], each=5) res <- basicPLM(pms, pns, TRUE, TRUE) res[['Estimates']][1:4, 1:3] res[['StdErrors']][1:4, 1:3] res[['Residuals']][1:20, 1:3]