makeSet: Initiate sets workflows
In rickhelmus/patRoon: Workflows for Mass-Spectrometry Based Non-Target Analysis

makeSet

R Documentation

Initiate sets workflows

Description

Initiate sets workflows from specified feature data.

Usage

makeSet(obj, ...)

## S4 method for signature 'features'
makeSet(obj, ..., adducts, labels = NULL)

## S4 method for signature 'featuresSet'
makeSet(obj, ...)

## S4 method for signature 'featureGroups'
makeSet(
  obj,
  ...,
  groupAlgo,
  groupArgs = NULL,
  verbose = TRUE,
  adducts = NULL,
  labels = NULL
)

## S4 method for signature 'featureGroupsSet'
makeSet(obj, ...)

Arguments

`obj`, `...`	`features` or `featureGroups` objects that should be used for the sets workflow.
`adducts`	The adduct assignments to each set. Should either be a `list` with `adduct` objects or a `character` vector (e.g. `"[M+H]+"`). The order should follow that of the objects given to the `obj` and `...` arguments. For the `featureGroups` method: if `NULL` then adduct annotations are used.
`labels`	The labels, or set names, for each set to be created. The order should follow that of the objects given to the `obj` and `...` arguments. If `NULL`, then labels are automatically generated from the polarity of the specified `adducts` argument (e.g. `"positive"`, `"negative"`).
`groupAlgo`	groupAlgo The name of the feature grouping algorithm. See the `algorithm` argument of `groupFeatures` for details.
`groupArgs`	A `list` with arguments directly passed to `groupFeatures` (can be named). Example: `groupArgs=list(maxAlignMZ=0.002)`.
`verbose`	If set to `FALSE` then no text output is shown.

Details

The makeSet method function is used to initiate a sets workflow. The features from input objects are combined and then neutralized by replacing their m/z values by neutral monoisotopic masses. After neutralization features measured with e.g. different ionization polarities can be grouped since their neutral mass will be the same.

The analysis information for this object is updated with all analyses, and a set column is added to designate the set of each analysis. Note that currently, all analyses names must be unique across different sets.

makeSet supports two types of input:

features objects: makeSet combines the input objects into a featuresSet object, which is then grouped in the 'usual way' with groupFeatures.
featureGroups objects: In this case the features from the input objects are first neutralized and feature groups between sets are then combined with groupFeatures.

The advantage of the featureGroups method is that it preserves any adduct annotations already present (e.g. as set by selectIons or adducts<-). Furthermore, this approach allows more advanced workflows where the input featureGroups are first pre-treated with e.g. filter before the sets object is made. On the other hand, the features method is easier, as it doesn't require intermediate feature grouping steps and is often sufficient since adduct annotations can be made afterwards with selectIons/adducts<- and most filter operations do not need to be done per individual set.

The adduct information used for feature neutralization is specified through the adducts argument. Alternatively, when the featureGroups method of makeSet is used, then the adduct annotations already present in the input objects can also by used by setting adducts=NULL. The adduct information is also used to add adduct annotations to the output of makeSet.