normalise_to_sum {pmp} | R Documentation

## 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)

[Package pmp version 1.4.0 Index]