Low-level function to estimate size factors with robust regression.
Given a matrix or data frame of count data, this function estimates the size
factors as follows: Each column is divided by the geometric means of the
rows. The median (or, if requested, another location estimator) of these
ratios (skipping the genes with a geometric mean of zero) is used as the size
factor for this column. Typically, one will not call this function directly, but use
estimateSizeFactors
.
estimateSizeFactorsForMatrix( counts, locfunc = stats::median, geoMeans, controlGenes, type = c("ratio", "poscounts") )
counts |
a matrix or data frame of counts, i.e., non-negative integer values |
locfunc |
a function to compute a location for a sample. By default, the
median is used. However, especially for low counts, the
|
geoMeans |
by default this is not provided, and the geometric means of the counts are calculated within the function. A vector of geometric means from another count matrix can be provided for a "frozen" size factor calculation |
controlGenes |
optional, numeric or logical index vector specifying those genes to use for size factor estimation (e.g. housekeeping or spike-in genes) |
type |
standard median ratio ( |
a vector with the estimates size factors, one element per column
Simon Anders
dds <- makeExampleDESeqDataSet() estimateSizeFactorsForMatrix(counts(dds)) geoMeans <- exp(rowMeans(log(counts(dds)))) estimateSizeFactorsForMatrix(counts(dds),geoMeans=geoMeans)
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