BlankFlag: Flag features based on the intensity in blank samples

In sneumann/xcms: LC-MS and GC-MS Data Analysis

Flag features based on the intensity in blank samples

Description

The 'BlankFlag' class and method enable users to flag features of an 'XcmsExperiment' or 'SummarizedExperiment' object based on the relationship between the intensity of a feature in blanks compared to the intensity in the samples.

This class and method are part of the possible dispatch of the generic function 'filterFeatures'. Features *below* ('<') the user-input threshold will be flagged by calling the 'filterFeatures' function. This means that an extra column will be created in 'featureDefinitions' or 'rowData' called 'possible_contaminants' with a logical value for each feature.

Usage

BlankFlag(
  threshold = 2,
  blankIndex = integer(),
  qcIndex = integer(),
  na.rm = TRUE
)

## S4 method for signature 'XcmsResult,BlankFlag'
filterFeatures(object, filter, ...)

## S4 method for signature 'SummarizedExperiment,BlankFlag'
filterFeatures(object, filter, assay = 1)

Arguments

threshold	'numeric' indicates the minimum difference required between the mean abundance of a feature in samples compared to the mean abundance of the same feature in blanks for it to not be considered a possible contaminant. For example, the default threshold of 2 signifies that the mean abundance of the features in samples has to be at least twice the mean abundance in blanks for it to not be flagged as a possible contaminant.
blankIndex	'integer' (or 'logical') vector corresponding to the indices of blank samples.
qcIndex	'integer' (or 'logical') vector corresponding to the indices of quality control (QC) samples.
na.rm	'logical' indicates whether missing values ('NA') should be removed prior to the calculations.
object	XcmsExperiment or SummarizedExperiment. For an XcmsExperiment object, the featureValues(object) will be evaluated, and for Summarizedesxperiment the assay(object, assay). The object will be filtered.
filter	The parameter object selecting and configuring the type of filtering. It can be one of the following classes: RsdFilter, DratioFilter, PercentMissingFilter or BlankFlag.
...	Optional parameters. For object being an XcmsExperiment: parameters for the featureValues() call.
assay	For filtering of SummarizedExperiment objects only. Indicates which assay the filtering will be based on. Note that the features for the entire object will be removed, but the computations are performed on a single assay. Default is 1, which means the first assay of the object will be evaluated.

Value

For 'BlankFlag': a 'BlankFlag' class. 'filterFeatures' returns the input object with an added column in the features metadata called 'possible_contaminants' with a logical value for each feature. This is added to 'featureDefinitions' for 'XcmsExperiment' objects and 'rowData' for 'SummarizedExperiment' objects.

Author(s)

Philippine Louail

See Also

Other Filter features in xcms: DratioFilter, PercentMissingFilter, RsdFilter

sneumann/xcms documentation built on Nov. 23, 2024, 6:53 p.m.