Flag features based on the intensity in blank samples

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 class 'XcmsResult,BlankFlag'
filterFeatures(object, filter, ...)

# S4 method for class '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.

See also

Other Filter features in xcms: DratioFilter, PercentMissingFilter, RsdFilter

Author

Philippine Louail