PsiNorm {scone} | R Documentation

## PsiNorm: scaling normalization based on the Pareto distribution

### Description

Normalization of a raw counts matrix using the estimate of the shape parameter of the Pareto distribution.

### Usage

    PsiNorm(x, ...)

    ## S4 method for signature 'SummarizedExperiment'
    PsiNorm(x, whichAssay = 1, assayName = "PsiNorm")

    ## S4 method for signature 'SingleCellExperiment'
    PsiNorm(x, whichAssay = "counts")

    ## S4 method for signature 'ANY'
    PsiNorm(x)

### Arguments

`x` | A SingleCellExperiment/SummarizedExperiment object or a matrix=like object with genes in rows and samples in columns.
`...` | generic argument
`whichAssay` | if x is a SingleCellExperiment/SummarizedExperiment the assay with the counts to normalize (default to 1).
`assayName` | if x is a SummarizedExperiment the name of the assay in which to save the normalized data (default to "PsiNorm").

### Value

If the input is a SingleCellExperiment object the function returns the same object adding as sizeFactors those computed by PsiNorm. If the object is a SummarizedExperiment object, the function returns the same object adding an assay with the normalized count matrix. If the input is a matrix-like object PsiNorm returns a matrix with the same dimensions containing the normalized counts.

### Author(s)

Matteo Borella and Davide Risso

### Examples

    m<-matrix(c(1,0,2,0,2,9,3,0), ncol=2)
    sce<-SingleCellExperiment::SingleCellExperiment(assays=list(counts=m))

    sce<-PsiNorm(sce) # SingleCellExperiment object
    norm.matrix<-PsiNorm(m) # normalized matrix object

[Package scone version 1.18.0 Index]