data.normalization: Data normalization

In CancerSubtypes: Cancer subtypes identification, validation and visualization based on multiple genomic data sets

Description

Conduct normalization for dataset.

Usage

data.normalization(Data, type = "feature_Median", log2 = FALSE)

Arguments

Data	A matrix representing the genomic data such as gene expression data, miRNA expression data. For the matrix, the rows represent the genomic features, and the columns represent the samples.
type	A character value representing the normalization type. The optional values are shown below: "feature_Median". The default value. Normalize dataset by sweeping the median values of each feature. "feature_Mean". Normalize dataset by sweeping the mean values of each feature. "feature_zscore". Conduct z_score normalization for each feature. "sample_zscore". Conduct z_score normalization for each samples.
log2	A logical value. If TRUE, the data is transform as log2(x+1). This is commonly used for RNAseq data.

Value

The normalized data matrix.

Examples

data(GeneExp)
result=data.normalization(GeneExp,type="feature_Median",log2=FALSE)

CancerSubtypes documentation built on Nov. 8, 2020, 8:24 p.m.