lmFit {limma} | R Documentation |
Fit linear model for each gene given a series of arrays
lmFit(object,design=NULL,ndups=1,spacing=1,block=NULL,correlation=0.75,weights=NULL,method="ls",...)
object |
object of class numeric , matrix , MAList , marrayNorm or exprSet containing log-ratios or log-values of expression for a series of microarrays |
design |
the design matrix of the microarray experiment, with rows corresponding to arrays and columns to coefficients to be estimated. Defaults to the unit vector meaning that the arrays are treated as replicates. |
ndups |
positive integer giving the number of times each gene is printed on an array |
spacing |
positive integer giving the spacing between duplicate spots, spacing=1 for consecutive spots |
block |
vector or factor specifying a blocking variable |
correlation |
the inter-duplicate or inter-technical replicate correlation |
weights |
optional numeric matrix containing weights for each spot |
method |
character string, "ls" for least squares or "robust" for robust regression |
... |
other optional arguments to be passed to lm.series , gls.series or rlm.series |
A linear model is fitted for each gene by calling one of lm.series
, gls.series
or rlm.series
.
Note that the arguments design
, ndups
, spacing
and weights
will be extracted from the data object
if available and do not normally need to set explicitly in the call.
If arguments are set in the call then they will over-ride slots or components in the data object
.
Object of class MArrayLM
Gordon Smyth
An overview of linear model functions in limma is given by 5.LinearModels.