mrlm {limma} | R Documentation |
Fit a linear model genewise to expression data from a series of arrays.
The fit is by robust M-estimation allowing for a small proportion of outliers.
This is a utility function for lmFit
.
mrlm(M,design=NULL,ndups=1,spacing=1,weights=NULL,...)
M |
numeric matrix containing log-ratio or log-expression values for a series of microarrays, rows correspond to genes and columns to arrays. |
design |
numeric design matrix defining the linear model, with rows corresponding to arrays and columns to comparisons to be estimated. The number of rows must match the number of columns of M . Defaults to the unit vector meaning that the arrays are treated as replicates. |
ndups |
a positive integer giving the number of times each gene is printed on an array. nrow(M) must be divisible by ndups . |
spacing |
the spacing between the rows of M corresponding to duplicate spots, spacing=1 for consecutive spots. |
weights |
numeric matrix of the same dimension as M containing weights. If it is of different dimension to M , it will be filled out to the same size. NULL is equivalent to equal weights. |
... |
any other arguments are passed to rlm.default . |
This is a utility function used by the higher level function lmFit
.
Most users should not use this function directly but should use lmFit
instead.
This function fits a linear model for each gene by calling the function rlm
from the MASS library.
Warning: don't use weights with this function unless you understand how rlm
treats weights.
The treatment of weights is somewhat different from that of lm.series
and gls.series
.
A list with components
coefficients |
numeric matrix containing the estimated coefficients for each linear model. Same number of rows as M , same number of columns as design . |
stdev.unscaled |
numeric matrix conformal with coef containing the unscaled standard deviations for the coefficient estimators. The standard errors are given by stdev.unscaled * sigma . |
sigma |
numeric vector containing the residual standard deviation for each gene. |
df.residual |
numeric vector giving the degrees of freedom corresponding to sigma . |
qr |
QR decomposition of design . |
Gordon Smyth
rlm
.
An overview of linear model functions in limma is given by 06.LinearModels.