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DESeq2 (version 1.6.3)

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
"normalizationFactors"(object)
"normalizationFactors"(object)<-value
"normalizationFactors"(object)

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()
normFactors <- matrix(runif(nrow(dds)*ncol(dds),0.5,1.5),
                      ncol=ncol(dds),nrow=nrow(dds))
normFactors <- normFactors / rowMeans(normFactors)
normalizationFactors(dds) <- normFactors
dds <- estimateDispersions(dds)
dds <- nbinomWaldTest(dds)

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