Normalization: Data Normalization

In stevexniu/scMatchmaker: Single Cell Matchmaker

Data Normalization

Description

Normalize count or other data.

Usage

Normalization(
  counts,
  normalization = c("logTPM", "cosine", "none"),
  normalize_factor = 10000,
  zero_percent = 0.7,
  verbose = FALSE
)

Arguments

counts	Data to normalize. An N x M matrix with N rows of features and M columns of data points.
normalization	Normalization method used. Default is cosine. logTPM, logged Transcript Per Million normalization: feature counts for each data point are divided by the total sum of them. Then the data is multiplied by the scale.factor before taking a log-transformed by log(1+x) (Default). cosine, cosine nomalization: feature counts for each data point are divided by their L2. none, additional normalization is not performed.
normalize_factor	Normalization factor used with lognorm method. Default is 10000.
zero_percent	Zero-entry percentage threshold. If the number of zero entries in the returned matrices is above this number, a sparse matrix will be returned. Default is 0.7 aka 70%.
verbose	Whether to display a process bar for cosine normalization. Default is FALSE.

Value

Returns the normalized data.

Examples

## Not run: 
normalized.data <- Normalization(data)

## End(Not run)

stevexniu/scMatchmaker documentation built on June 2, 2022, 12:35 p.m.