norm.data: Normalize data

In rezakj/scSeqR: scSeqR; a toolkit to analyze single cell sequencing data types (i.e scRNA-seq) and large numeric matrix files.

Normalize data

Description

This function takes an object of class scSeqR and normalized the data based on "global.glsf", "ranked.glsf" or "spike.in" methods.

Usage

norm.data(x = NULL, norm.method = "ranked.glsf", top.rank = 500,
  spike.in.factors = NULL, rpm.factor = 1000)

Arguments

x	An object of class scSeqR.
norm.method	Choose a normalization method, there are three option currently. Choose from "global.glsf", "ranked.glsf", "rpm","spike.in" or no.norm, defult = "ranked.glsf".
top.rank	If the method is set to "ranked.glsf", you need to set top number of genes sorted based on global base mean, defult = 500.
rpm.factor	If the norm.method is set to "rpm" the library sizes would be diveded by this number, defults = 1000 (higher numbers recomanded for bulk RNA-Seq).

Value

An object of class scSeqR.

Examples

## Not run: 
my.obj <- norm.data(my.obj,
                   norm.method = "ranked.glsf",
                   top.rank = 500) # best for scRNA-Seq

my.obj <- norm.data(my.obj, norm.method = "global.glsf") # best for bulk RNA-Seq
my.obj <- norm.data(my.obj, norm.method = "rpm", rpm.factor = 100000) # best for bulk RNA-Seq
my.obj <- norm.data(my.obj, norm.method = "spike.in", spike.in.factors = NULL)
my.obj <- norm.data(my.obj, norm.method = "no.norm") # if the data is already normalized

## End(Not run)

rezakj/scSeqR documentation built on March 28, 2022, 12:17 p.m.