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Feature group to table conversion

Source: R/feature_groups-ADT.R
feature-table.Rd

Convert feature group data to a data.table (or data.frame).

Usage

# S4 method for class 'featureGroups'
as.data.table(
  x,
  average = FALSE,
  areas = FALSE,
  features = FALSE,
  qualities = FALSE,
  regression = FALSE,
  regressionBy = NULL,
  averageFunc = mean,
  normalized = FALSE,
  FCParams = NULL,
  concAggrParams = getDefPredAggrParams(),
  toxAggrParams = getDefPredAggrParams(),
  normConcToTox = FALSE,
  anaInfoCols = NULL,
  IMS = "both"
)

# S4 method for class 'featureGroupsScreening'
as.data.table(x, ..., collapseSuspects = ",", onlyHits = FALSE)

# S4 method for class 'featureGroupsScreeningSet'
as.data.table(x, ..., collapseSuspects = ",", onlyHits = FALSE)

Arguments

x

The featureGroups like object to be exported as table.

average

Controls the averaging of feature intensities. Averaging also influences the calculation of regression parameters. Set to FALSE to disable averaging, TRUE to average per replicate or to the name of a column in the analysis information to compare by a custom grouping of analyses.

If features=TRUE all numerical properties are averaged and non-numericals are collapsed. Each row represents the feature aggregated data and the groups used for aggregation (e.g. replicates) are stored in the average_group column. It is also possible to average these data per feature group, by setting average="fGroups".

areas

If set to TRUE then areas are output instead of peak intensities. Ignored if features=TRUE, as areas of features are always reported.

features

If TRUE then feature specific data will be added. Also see the average argument.

qualities

Adds feature (group) qualities (qualities="quality"), scores (qualities="score") or both (qualities="both"), if this data is available (i.e. from calculatePeakQualities). If qualities=FALSE then nothing is reported.

regression, regressionBy

Used for regression calculations. See the Regression calculation section below. Set to NULL to ignore.

averageFunc

Function used for averaging. Only used when data is averaged or FCParams != NULL.

normalized

If TRUE then normalized intensities are used (see the Feature intensity normalization section). If no normalization data is available (e.g. because normInts was not used) then an automatic group normalization is performed.

FCParams

A parameter list to calculate fold change data. See getFCParams for more details. Set to NULL to not perform FC calculations. NOTE: the intensity data is always averaged to calculate fold changes (using averageFunc) by replicates, irrespective of the average argument.

concAggrParams, toxAggrParams

Parameters to aggregate calculated concentrations/toxicities (obtained with calculateConcs/calculateTox). See prediction aggregation parameters for more information. Set to NULL to omit this data.

normConcToTox

Set to TRUE to normalize concentrations to toxicities. Only relevant if this data is present (see calculateConcs/calculateTox).

anaInfoCols

A character with any additional columns from the analysis information table. Only supported if features=TRUE. If averaging is performed, then numeric data is averaged and character data collapsed. Set to NULL to ignore.

IMS

(IMS workflow) Specifies which feature groups are considered to be returned in IMS workflows. The following options are valid:

  • "both": Selects IMS and non-IMS features.

  • "maybe": Selects non-IMS features and IMS features without assigned IMS precursor.

  • FALSE: Selects only non-IMS features.

  • TRUE: Selects only IMS features.

...

Passed to the parent as.data.table method.

collapseSuspects

If a character then any suspects that were matched to the same feature group are collapsed to a single row and suspect names are separated by the value of collapseSuspects. If NULL then no collapsing occurs, and each suspect match is reported on a single row. See the Suspect collapsing section below for additional details.

onlyHits

If TRUE then only feature groups with suspect hits are reported.

Details

The as.data.table generic function converts most feature group data to a highly customizable data.table. If a classical data.frame is preferred, the as.data.frame generic function can be used instead and accepts the exact same arguments. The methods defined for suspect screening workflows will merge the information from screenInfo, such as suspect names and other properties and annotation data.

Regression calculation

The regression argument controls the calculation of regression parameters from a regression model calculated with feature intensities (or areas if areas=TRUE). Here, simple linear regression is used, i.e. y=ax+b with a the slope and b the intercept. The value for regression should be the name of a column in the analysis information table with numerical data to be used for x-values. Alternatively, if regression=TRUE then the "conc" column is used. Any NA x-values are ignored, and no regression will be calculated if less than two (non-NA) x-values are available. The output table will contain properties such as the slope and correlation coefficient (R-squared). Furthermore, if features=TRUE then x-values will be calculated from the model and stored in the x_reg column.

The regressionBy argument can be used to construct separate regression models for different groups of analysis. It should be set to the name of a column in the analysis information table which defines the grouping between samples. If features=TRUE then the grouping is stored in the regression_group column of the output table.

Please see the handbook for examples on how to use the regression functionality.

Suspect collapsing

The as.data.table method for featureGroupsScreening supports an additional format where each suspect hit is reported on a separate row (enabled by setting collapseSuspects=NULL). In this format the suspect properties from the screenInfo method are merged with each suspect row. Alternatively, if suspect collapsing is enabled (the default) then the regular as.data.table format is used, and amended with the names and estimated ID levels (if available) of the suspects matched to a feature group (each separated by the value of the collapseSuspects argument).

Suspect collapsing also influences the reporting of predicted feature concentrations and toxicities. In the case that (1) suspects are not collapsed in the output table and (2) predictions are available for a specific suspect hit (i.e. if predictRespFactors or predictTox was called on the feature groups object), then only the suspect specific data is reported and no aggregation is performed. Hence, this allows you to obtain specific concentration/toxicity values for each suspect/feature group pair.

IMS workflows

If the IMS argument is set to "both" or "maybe" then "mobility_collapsed" and "CCS_collapsed" columns will be added that summarize all mobility/CCS values of the IMS features (or IMS feature groups) assigned to this IMS precursor. These numbers are currently rounded to 3 decimals.

Sets workflows

In a sets workflow normalization of feature intensities occur per set.

In sets workflows the analysis information contains an additional "set" column, which can be used for arguments that involve grouping of analyses. For instance, if regressionBy="set" then regression models will be calculated for each set.