Normalization: Normalisation of features

In MosaiClusteR: An Umbrella Framework for Multi-Source and Multi-Omics Clustering

Normalisation of features

Description

When data of different scales are combined it is recommended to normalise so that the structures are comparable.

Usage

Normalization(
  Data,
  method = c("Quantile", "Fisher-Yates", "Standardize", "Range", "Q", "q", "F", "f", "S",
    "s", "R", "r")
)

Arguments

Data	A data matrix; rows are assumed to correspond to the objects.
method	One of "Quantile", "Fisher-Yates", "Standardize", "Range" (or any unambiguous first letter).

Details

"Quantile" performs quantile normalisation (common in omics); "Fisher-Yates" uses normal scores based only on the number of rows; "Standardize" centres and scales each column (base scale); "Range" maps the matrix to [0, 1].

Value

The normalised matrix.

Examples

x <- matrix(rnorm(100), 10, 10)
Norm_x <- Normalization(x, method = "R")

MosaiClusteR documentation built on Oct. 25, 2026, 1:08 a.m.