# estimateSizeFactorsForMatrix

0th

Percentile

##### 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.

##### Usage
estimateSizeFactorsForMatrix(counts, locfunc = stats::median, geoMeans, controlGenes)
##### Arguments
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 shorth function from genefilter may give better results.
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)
##### Value

a vector with the estimates size factors, one element per column

estimateSizeFactors

##### Aliases
• estimateSizeFactorsForMatrix
##### Examples

dds <- makeExampleDESeqDataSet()
estimateSizeFactorsForMatrix(counts(dds))
geoMeans <- exp(rowMeans(log(counts(dds))))
estimateSizeFactorsForMatrix(counts(dds),geoMeans=geoMeans)


Documentation reproduced from package DESeq2, version 1.12.3, License: LGPL (>= 3)

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