PLMset-class {affyPLM} | R Documentation

## Class PLMset

### Description

This is a class representation for Probe level Linear Models fitted to Affymetrix GeneChip probe level data.

### Objects from the Class

Objects can be created using the function `fitPLM`

### Slots

`probe.coefs`:

  Object of class "matrix". Contains model coefficients related to probe effects.

`se.probe.coefs`:

  Object of class "matrix". Contains standard error estimates for the probe coefficients.

`chip.coefs`:

  Object of class "matrix". Contains model coefficients related to chip (or chip level) effects for each fit.

`se.chip.coefs`:

  Object of class "matrix". Contains standard error estimates for the chip coefficients.

`const.coefs`:

  Object of class "matrix". Contains model coefficients related to intercept effects for each fit.

`se.const.coefs`:

  Object of class "matrix". Contains standard error estimates for the intercept estimates

`model.description`:

  Object of class "character". This string describes the probe level model fitted.

`weights`:

  List of objects of class "matrix". Contains probe weights for each fit. The matrix has columns for chips and rows are probes.

`phenoData`:

  Object of class "phenoData" This is an instance of class `phenoData` containing the patient (or case) level data. The columns of the pData slot of this entity represent variables and the rows represent patients or cases.

`annotation`

  A character string identifying the annotation that may be used for the `ExpressionSet` instance.

`experimentData`:

  Object of class "MIAME". For compatibility with previous version of this class description can also be a "character". The class `characterOrMIAME` has been defined just for this.

`cdfName`:

  A character string giving the name of the cdfFile.

`nrow`:

  Object of class "numeric". Number of rows in chip.

`ncol`:

  Object of class "numeric". Number of cols in chip.

`narrays`:

  Object of class "numeric". Number of arrays used in model fit.

`normVec`:

  Object of class "matrix". For storing normalization vector(s). Not currentl used

`varcov`:

  Object of class "list". A list of variance/covariance matrices.

`residualSE`:

  Object of class "matrix". Contains residual standard error and df.

`residuals`:

  List of objects of class "matrix". Contains residuals from model fit (if stored).

`model.call`:

  Object of class "call"

### Methods

weights<-

  `signature(object = "PLMset")`: replaces the weights.

weights

  `signature(object = "PLMset")`: extracts the model fit weights.

coefs<-

  `signature(object = "PLMset")`: replaces the chip coefs.

coefs

  `signature(object = "PLMset")`: extracts the chip coefs.

se

  `signature(object = "PLMset")`: extracts the standard error estimates of the chip coefs.

se<-

  `signature(object = "PLMset")`: replaces the standard error estimates of the chip coefs.

coefs.probe

  `signature(object = "PLMset")`: extracts the probe coefs.

se.probe

  `signature(object = "PLMset")`: extracts the standard error estimates of the probe coefs.

coefs.const

  `signature(object = "PLMset")`: extracts the intercept coefs.

se.const

  `signature(object = "PLMset")`: extracts the standard error estimates of the intercept coefs.

getCdfInfo

  `signature(object = "PLMset")`: retrieve the environment that defines the location of probes by probe set.

image

  `signature(x = "PLMset")`: creates an image of the robust linear model fit weights for each sample.

indexProbes

  `signature(object = "PLMset", which = "character")`: returns a list with locations of the probes in each probe set. The list names defines the probe set names. `which` can be "pm", "mm", or "both". If "both" then perfect match locations are given followed by mismatch locations.

Mbox

  `signature(object = "PLMset")`: gives a boxplot of M's for each chip. The M's are computed relative to a "median" chip.

normvec

  `signature(x = "PLMset")`: will return the normalization vector (if it has been stored).

residSE

  `signature(x = "PLMset")`: will return the residual SE (if it has been stored).

boxplot

  `signature(x = "PLMset")`: Boxplot of Normalized Unscaled Standard Errors (NUSE).

NUSE

  `signature(x = "PLMset")` : Boxplot of Normalized Unscaled Standard Errors (NUSE) or NUSE values.

RLE|

  `signature(x = "PLMset")` : Relative Log Expression boxplot or values.

### Note

This class is better described in the vignette.

### Author(s)

B. M. Bolstad bmb@bmbolstad.com

### References

Bolstad, BM (2004) Low Level Analysis of High-density Oligonucleotide Array Data: Background, Normalization and Summarization. PhD Dissertation. University of California, Berkeley.

[Package affyPLM version 1.64.0 Index]