norm.data: Normalize data
In rezakj/iCellR: Analyzing High-Throughput Single Cell Sequencing Data

norm.data

R Documentation

Normalize data

Description

This function takes an object of class iCellR 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,
  rounding.digits = 3,
  round.num = TRUE,
  ATAC.data = FALSE,
  ATAC.filter = TRUE
)

Arguments

`x`	An object of class iCellR.
`norm.method`	Choose a normalization method, there are three option currently. Choose from "global.glsf", "ranked.glsf","spike.in" or no.norm, default = "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, default = 500.
`spike.in.factors`	A numeric vector of spike-in values with the same cell id order as the main data.
`rpm.factor`	If the norm.method is set to "rpm" the library sizes would be divided by this number, default = 1000 (higher numbers recomanded for bulk RNA-Seq).
`rounding.digits`	integer indicating the number of decimal places (round) or significant digits (signif) to be used.
`round.num`	Rounding of Numbers, default = FALSE.
`ATAC.data`	If TURE, it would normalize ATAC-Seq data and not RNA-Seq, default = FALSE.
`ATAC.filter`	If TURE, all the cells filtered in RNA-Seq will be filtered in ATAC-Seq. This needs to be done for both data to match, default = TRUE.