normalizationFactor {DSS} | R Documentation |
The normalization factors are used to adjust for technical or biological biases in the sequencing experiments. The factors can either be (1) a vector with length equals to the number of columns of the count data; or (2) a matrix with the same dimension of the count data.
## S4 method for signature 'SeqCountSet' normalizationFactor(object) ## S4 replacement method for signature 'SeqCountSet,numeric' normalizationFactor(object) <- value ## S4 replacement method for signature 'SeqCountSet,matrix' normalizationFactor(object) <- value
object |
A SeqCountData object. |
value |
A numeric vector or matrix. If it is a vector it must have length equals to the number of columns of the count data. For matrix it must have the same dimension of the count data. |
The vector normalization factors are used mostly to correct for sequencing depth from different datasets. The matrix factor applies a different normalizing constant for each gene at each sample to adjust for a broader range of artifacts such as GC content.
Hao Wu <hao.wu@emory.edu>
dispersion
data(seqData) ## obtain nomalization factor seqData=estNormFactors(seqData, "quantile") normalizationFactor(seqData) ## assign as vector normalizationFactor(seqData)=rep(1, ncol(exprs(seqData))) ## getan error here ## or assign as a matrix f=matrix(1, nrow=nrow(exprs(seqData)), ncol=ncol(exprs(seqData))) normalizationFactor(seqData)=f