PLMset-class {affyPLM} | R Documentation |

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
`model.description`

:- Object of class "character". This string describes the probe level model fitted.
`weights`

:- Object 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
`exprSet`

instance. `description`

:- 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
`notes`

:- Object of class "character" Vector of explanatory text
`varcov`

:- Object of class "list". A list of variance/covariance matrices
`residualSE`

:- Object of class "matrix". Contains residual standard error and df
`residuals`

:- Object of class "matrix". Contains residuals from model fit (if stored)

Class `"exprSet"`

, directly.

- 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 bolstad@stat.berkeley.edu

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 1.6.0 Index]