Normalize Data (original) (raw)

NormalizeData: Normalize Data

View source: R/generics.R

NormalizeData R Documentation

Description

Normalize the count data present in a given assay.

Usage

NormalizeData(object, ...)

## S3 method for class 'V3Matrix'
NormalizeData(
  object,
  normalization.method = "LogNormalize",
  scale.factor = 10000,
  margin = 1,
  block.size = NULL,
  verbose = TRUE,
  ...
)

## S3 method for class 'Assay'
NormalizeData(
  object,
  normalization.method = "LogNormalize",
  scale.factor = 10000,
  margin = 1,
  verbose = TRUE,
  ...
)

## S3 method for class 'Seurat'
NormalizeData(
  object,
  assay = NULL,
  normalization.method = "LogNormalize",
  scale.factor = 10000,
  margin = 1,
  verbose = TRUE,
  ...
)

Arguments

object An object
... Arguments passed to other methods
normalization.method Method for normalization. “LogNormalize”: Feature counts for each cell are divided by the total counts for that cell and multiplied by thescale.factor. This is then natural-log transformed using log1p “CLR”: Applies a centered log ratio transformation “RC”: Relative counts. Feature counts for each cell are divided by the total counts for that cell and multiplied by thescale.factor. No log-transformation is applied. For counts per million (CPM) set scale.factor = 1e6
scale.factor Sets the scale factor for cell-level normalization
margin If performing CLR normalization, normalize across features (1) or cells (2)
block.size How many cells should be run in each chunk, will try to split evenly across threads
verbose display progress bar for normalization procedure
assay Name of assay to use

Value

Returns object after normalization

Examples

## Not run: 
data("pbmc_small")
pbmc_small
pmbc_small <- NormalizeData(object = pbmc_small)

## End(Not run)

Seurat documentation built on June 8, 2025, 12:24 p.m.