Parameters to aggregate concentrations/toxicity values assigned to feature groups

Parameters that are used by method functions such as.data.table to aggregate predicted concentrations or toxicities.

getDefPredAggrParams(all = mean, ...)

Arguments

all

The default aggregation function for all types, e.g. mean.

...

optional named arguments that override defaults.

Details

Multiple concentration or toxicity values may be assigned to a single feature group. To ease the interpretation and data handling, several functions aggregate these values prior their use. Aggregation occurs by the following data:

• The candidate (i.e. suspect or annotation candidate). This is mainly relevant for sets workflows, where calculations among sets may yield different results for the same candidate.

• The prediction type, e.g. all values that were obtained from suspect or compound annotation data.

• The feature group.

The aggregation of all data first occurs by the same candidate/type/feature group, then the same type/feature group and finally for each feature group. This ensures that e.g. large numbers of data points for a prediction type do not bias results.

The candidateFunc, typeFunc and groupFunc parameters specify the function that should be used to aggregate data. Commonly, functions such mean, min or max can be used here. Note that the function does not need to handle NA values, as these are removed in advance.

The preferType parameters specifies the preferred prediction type. Any values from other prediction types will be ignored unless the preferred type is not available for a feature group. Valid values are "suspect" (the default), "compound" (results from compound annotation by SMILES), "SIRIUS_FP" (results from formula/compound annotation with SIRIUS+CSI:FingerID) or "none".

These parameters should be stored inside a list. The getDefPredAggrParams function can be used to generate such parameter list with defaults.