normalise_to_sum: Normalisation by total sum of the features per sample

In computational-metabolomics/pmp: Peak Matrix Processing and signal batch correction for metabolomics datasets

Normalisation by total sum of the features per sample

Description

For each sample, every feature intensity value is divided by the total sum of all feature intensity values measured in that sample (NA values ignored by default), before multiplication by 100; the unit is %.

Usage

normalise_to_sum(df, check_df = TRUE)

Arguments

df	A matrix-like (e.g. an ordinary matrix, a data frame) or RangedSummarizedExperiment-class object with all values of class numeric() or integer() of peak intensities, areas or other quantitative characteristic.
check_df	logical(1), if set to TRUE will check if input data needs to be transposed, so that features are in rows.

Value

Object of class SummarizedExperiment. If input data are a matrix-like (e.g. an ordinary matrix, a data frame) object, function returns the same R data structure as input with all value of data type numeric().

Examples

df <- MTBLS79[ ,MTBLS79$Batch == 1]
out <- normalise_to_sum (df=df)

computational-metabolomics/pmp documentation built on March 9, 2024, 4:25 p.m.