zeroone_norm: Zero-one normalization

In greenelab/ADAGEpath: ADAGE-based Signature Analysis

Zero-one normalization

Description

Normalizes gene expression values in the input_data to be between 0 and 1. Normalization is done per gene (row-wise) through subtracting row minimum from each value and then being divided by row range. If using reference, the normalization is done using a gene's expression minimum and range in the reference data.

Usage

zeroone_norm(input_data, use_ref = FALSE, ref_data)

Arguments

input_data	a data.frame with gene IDs in the first column and expression values from the second column.
use_ref	a logical value indicating whether the normalization should be done based on the reference data (default: FALSE).
ref_data	a data.frame storing gene expression values to be used as a reference dataset for zero-one normalization. The first columns in input_data and ref_data that specify gene IDs should be exactly the same.

Value

a data.frame storing zero-one normalized gene expression values from the input_data.

greenelab/ADAGEpath documentation built on May 25, 2022, 7:11 a.m.