iCellR (version 1.6.4)

norm.data: 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.

Value

An object of class iCellR.

Examples

# NOT RUN {
demo.obj <- norm.data(demo.obj, norm.method = "ranked.glsf", top.rank = 500)

# }