scaleNormMultCont {SCnorm} | R Documentation

## Scale multiple conditions

### Description

After conditions are independently normalized with the count-depth effect removed, conditions need to be additionally scaled prior to further analysis. Genes that were normalized in both conditions are split into quartiles based on their un-normalized non-zero medians. Genes in each quartile are scaled to the median fold change of condition specific gene means and overall gene means.

### Usage

    scaleNormMultCont(NormData, OrigData, Genes, useSpikes, useZerosToScale)

### Arguments

`NormData` | list of matrices of normalized expression counts and scale factors for each condition. Matrix rows are genes and columns are samples.
`OrigData` | list of matrices of un-normalized expression counts. Matrix rows are genes and columns are samples. Each item in list is a different condition.
`Genes` | vector of genes that will be used to scale conditions, only want to use genes that were normalized.
`useSpikes` | whether to use spike-ins to perform between condition scaling (default=FALSE). Assumes spike-in names start with "ERCC-".
`useZerosToScale` | whether to use zeros when scaling across conditions (default=FALSE).

### Value

matrix of normalized and scaled expression values for all conditions.

### Author(s)

Rhonda Bacher

[Package SCnorm version 1.2.1 Index]