normalizationFactors: Accessor functions for the normalization factors in a DESeqDataSet object.

Description

Gene-specific normalization factors for each sample can be provided as a matrix, which will preempt sizeFactors. In some experiments, counts for each sample have varying dependence on covariates, e.g. on GC-content for sequencing data run on different days, and in this case it makes sense to provide gene-specific factors for each sample rather than a single size factor.

Usage

normalizationFactors(object, ...)
normalizationFactors(object, ...) <- value
## S3 method for class 'DESeqDataSet':
normalizationFactors(object)
## S3 method for class 'DESeqDataSet,matrix':
normalizationFactors(object) <- value

Arguments

object

a DESeqDataSet object.

...

additional arguments

value

the matrix of normalization factors

Details

Normalization factors alter the model of DESeq in the following way, for counts $K_{ij}$ and normalization factors $NF_{ij}$ for gene i and sample j:

$$K_{ij} \sim \textrm{NB}( \mu_{ij}, \alpha_i)$$ $$\mu_{ij} = NF_{ij} q_{ij}$$

Examples

Run this code

dds <- makeExampleDESeqDataSet(n=100, m=4)

normFactors <- matrix(runif(nrow(dds)*ncol(dds),0.5,1.5),
                      ncol=ncol(dds),nrow=nrow(dds),
                      dimnames=list(1:nrow(dds),1:ncol(dds)))

# the normalization factors matrix should not have 0's in it
# it should have geometric mean near 1 for each row
normFactors <- normFactors / exp(rowMeans(log(normFactors)))
normalizationFactors(dds) <- normFactors

dds <- DESeq(dds)

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