myvoom: myvoom function
In ntyet/rmRNAseq: RNA-Seq Analysis for Repeated-Measures Data

myvoom

R Documentation

myvoom function

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,
  ...
)

`counts`	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`	design matrix with rows corresponding to samples and columns to coefficients to be estimated. Defaults to `model.matrix(~0+counts$samples$group)` if `counts` is a DGEList, otherwise defaults to the unit vector meaning that all samples are treated as replicates.
`lib.size`	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.
`normalize.method`	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"`.
`span`	width of the smoothing window used for the lowess mean-variance trend. Expressed as a proportion between 0 and 1.
`plot`	logical, should a plot of the mean-variance trend be displayed?
`save.plot`	logical, should the coordinates and line of the plot be saved in the output?