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

Objects can be created using the function `fitPLM`

`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"

- 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.

This class is better described in the vignette.

B. M. Bolstad bmb@bmbolstad.com

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

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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