This function modifies the original voom function
to obtain the fitted function f of the lowess fit.
myvoom(counts, design = NULL, lib.size = NULL,
normalize.method = "none", span = 0.5, plot = FALSE,
save.plot = FALSE, ...)a numeric matrix containing raw counts, or an ExpressionSet containing raw counts, or a DGEList object. Counts must be non-negative and NAs are not permitted.
design matrix with rows corresponding to samples and columns to coefficients to be estimated. Defaults to the unit vector meaning that samples are treated as replicates.
numeric vector containing total library sizes for each sample.
Defaults to the normalized (effective) library sizes in counts if counts is a DGEList or
to the columnwise count totals if counts is a matrix.
the microarray-style normalization method to be applied to the logCPM values (if any).
Choices are as for the method argument of normalizeBetweenArrays when the data is single-channel.
Any normalization factors found in counts will still be used even if normalize.method="none".
width of the lowess smoothing window as a proportion.
logical, should a plot of the mean-variance trend be displayed?
logical, should the coordinates and line of the plot be saved in the output?
other arguments are passed to lmFit.
the same output as voom plus the fitted function f
of the lowess fit of the link[limma]{voom} method.