feature-grouping {xcms} | R Documentation

## Compounding of LC-MS features

### Description

Feature compounding aims at identifying and grouping LC-MS features representing different ions or adducts (including isotopes) of the same originating compound. The MsFeatures package provides a general framework and functionality to group features based on different properties. The `groupFeatures` methods for XCMSnExp objects implemented in `xcms` extend these to enable the compounding of LC-MS data. Note that these functions simply define feature groups but don't actually aggregate or combine the features.

See `MsFeatures::groupFeatures()` for an overview on the general feature grouping concept as well as details on the individual settings and parameters.

The available options for `groupFeatures` on `xcms` preprocessing results (i.e. on `XCMSnExp` objects after correspondence analysis with `groupChromPeaks()`) are:

- Grouping by similar retention times: `groupFeatures-similar-rtime()`.

- Grouping by similar feature values across samples: `AbundanceSimilarityParam()`.

- Grouping by similar peak shape of extracted ion chromatograms: `EicSimilarityParam()`.

An ideal workflow grouping features should sequentially perform the above methods (in the listed order).

Compounded feature groups can be accessed with the `featureGroups` function.

### Usage

    ## S4 method for signature 'XCMSnExp'
    featureGroups(object)

    ## S4 replacement method for signature 'XCMSnExp'
    featureGroups(object) <- value

### Arguments

`object` | an `XCMSnExp()` object.
`value` | for `featureGroups<-`: replacement for the feature groups in `object`. Has to be of length 1 or length equal to the number of features in `object`.

### Author(s)

Johannes Rainer, Mar Garcia-Aloy, Vinicius Veri Hernandes

### See Also

`plotFeatureGroups()` for visualization of grouped features.

[Package xcms version 3.16.1 Index]