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
:se.probe.coefs
:chip.coefs
:se.chip.coefs
:model.description
:weights
:phenoData
: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
ExpressionSet
instance.description
:characterOrMIAME
has been
defined just for this.cdfName
:nrow
:ncol
:notes
:varcov
:residualSE
:residuals
:signature(object = "PLMset")
: replaces the weights.signature(object = "PLMset")
: extracts the
model fit weights.signature(object = "PLMset")
: replaces the
chip coefs.signature(object = "PLMset")
: extracts the
chip coefs.signature(object = "PLMset")
: extracts the
standard error estimates of the chip coefs.signature(object = "PLMset")
: replaces the
standard error estimates of the chip coefs.signature(object = "PLMset")
: extracts the
probe coefs.signature(object = "PLMset")
: extracts the
standard error estimates of the probe coefs.signature(object = "PLMset")
: extracts the
intercept coefs.signature(object = "PLMset")
: extracts the
standard error estimates of the intercept coefs.signature(object = "PLMset")
: retrieve
the environment that defines the location of probes by probe set.signature(x = "PLMset")
: creates an image
of the robust linear model fit weights for each sample.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.signature(object = "PLMset")
: gives a boxplot of
M's for each chip. The M's are computed relative to a "median"
chip.signature(x = "PLMset")
: will return the normalization vector
(if it has been stored).signature(x = "PLMset")
: will return the residual SE
(if it has been stored).signature(x = "PLMset")
: Boxplot of Normalized
Unscaled Standard Errors (NUSE).signature(x = "PLMset")
: Boxplot of Normalized
Unscaled Standard Errors (NUSE) or NUSE values.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.