basicPLM {oligo} | R Documentation

## Simplified interface to PLM.

### Description

Simplified interface to PLM.

### Usage

    basicPLM(pmMat, pnVec, normalize = TRUE, background = TRUE, transfo =
      log2, method = c('plm', 'plmr', 'plmrr', 'plmrc'), verbose = TRUE)

### Arguments

`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.

### Value

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.

### Note

Currently, only RMA-bg-correction and quantile normalization are allowed.

### Author(s)

Benilton Carvalho

### See Also

`rcModelPLM`, `rcModelPLMr`, `rcModelPLMrr`, `rcModelPLMrc`, `basicRMA`

### Examples

    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]

[Package oligo version 1.52.1 Index]