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Class for suspect screened feature groups.

Source: R/generics.R, R/feature_groups-screening.R, R/feature_groups-screening-set.R
featureGroupsScreening-class.Rd

This class derives from featureGroups and adds suspect screening information.

Usage

screenInfo(obj)

# S4 method for class 'featureGroupsScreening'
screenInfo(obj)

# S4 method for class 'featureGroupsScreening'
show(object)

# S4 method for class 'featureGroupsScreening,ANY,ANY,missing'
x[i, j, ..., suspects = NULL, reorder = FALSE, drop = TRUE]

# S4 method for class 'featureGroupsScreening'
delete(obj, i = NULL, j = NULL, k = NULL, ...)

# S4 method for class 'featureGroupsScreening'
filter(
  obj,
  ...,
  onlyHits = NULL,
  IMSMatchParams = NULL,
  selectHitsBy = NULL,
  selectBestFGroups = FALSE,
  maxLevel = NULL,
  maxFormRank = NULL,
  maxCompRank = NULL,
  minAnnSimForm = NULL,
  minAnnSimComp = NULL,
  minAnnSimBoth = NULL,
  absMinFragMatches = NULL,
  relMinFragMatches = NULL,
  minRF = NULL,
  maxLC50 = NULL,
  negate = FALSE,
  applyIMS = "both"
)

# S4 method for class 'featureGroupsScreeningSet'
screenInfo(obj)

# S4 method for class 'featureGroupsScreeningSet'
show(object)

# S4 method for class 'featureGroupsScreeningSet,ANY,ANY,missing'
x[i, j, ..., suspects = NULL, sets = NULL, reorder = FALSE, drop = TRUE]

# S4 method for class 'featureGroupsScreeningSet'
delete(obj, i = NULL, j = NULL, k = NULL, ...)

# S4 method for class 'featureGroupsScreeningSet'
filter(
  obj,
  ...,
  onlyHits = NULL,
  IMSMatchParams = NULL,
  selectHitsBy = NULL,
  selectBestFGroups = FALSE,
  maxLevel = NULL,
  maxFormRank = NULL,
  maxCompRank = NULL,
  minAnnSimForm = NULL,
  minAnnSimComp = NULL,
  minAnnSimBoth = NULL,
  absMinFragMatches = NULL,
  relMinFragMatches = NULL,
  minRF = NULL,
  maxLC50 = NULL,
  negate = FALSE,
  applyIMS = "both"
)

# S4 method for class 'featureGroupsScreeningSet'
unset(obj, set)

Arguments

obj, object, x

The featureGroupsScreening object.

i, j, reorder

See featureGroups.

...

Further arguments passed to the base method.

suspects

An optional character vector with suspect names. If specified, only featureGroups will be kept that are assigned to these suspects.

drop

Ignored.

k

The k argument is used to delete screening results (instead of features) and should be:

  • a character vector with suspect names that should be removed

  • a function that is called with the screening info table and should return a logical vector for each suspect row to be removed

  • NA to remove all screening results, which is especially useful when paired with the j argument, i.e. to remove all screening results for a particular set of feature groups.

  • NULL to not touch screening results and only perform deletion as the featureGroups method.

Setting both i and k is currently not supported.

onlyHits

If

  • negate=FALSE and onlyHits=TRUE then all feature groups without suspect hits will be removed. Otherwise nothing will be done.

  • negate=TRUE then onlyHits=TRUE will select feature groups without suspect hits, onlyHits=FALSE will only retain feature groups with suspect matches and this filter is ignored if onlyHits=NULL.

IMSMatchParams

(IMS workflow) A list with parameters to be used for matching IMS data. See getIMSMatchParams for details and how to make such a parameter list.

selectHitsBy

Should be "intensity" or "level". For cases where the same suspect is matched to multiple feature groups, only the suspect to the feature group with highest mean intensity (selectHitsBy="intensity") or best identification level (selectHitsBy="level") is kept. In case of ties only the first hit is kept. Set to NULL to ignore this filter. If negate=TRUE then only those hits with lowest mean intensity/poorest identification level are kept.

selectBestFGroups

If TRUE then for any cases where a single feature group is matched to several suspects only the suspect assigned to the feature group with best identification score is kept. In case of ties only the first is kept.

maxLevel, maxFormRank, maxCompRank, minAnnSimForm, minAnnSimComp, minAnnSimBoth

Filter suspects by maximum identification level (e.g. "3a"), formula/compound rank or with minimum formula/compound/combined annotation similarity. Set to NULL to ignore.

absMinFragMatches, relMinFragMatches

Only retain suspects with this minimum number MS/MS matches with the fragments specified in the suspect list (i.e. fragments_mz/fragments_formula). relMinFragMatches sets the minimum that is relative (0-1) to the maximum number of MS/MS fragments specified in the fragments_* columns of the suspect list. Set to NULL to ignore.

minRF

Filter suspect hits by the given minimum predicted response factor (as calculated by predictRespFactors). Set to NULL to ignore.

maxLC50

Filter suspect hits by the given maximum toxicity (LC50) (as calculated by predictTox). Set to NULL to ignore.

negate

If set to TRUE then filtering operations are performed in opposite manner.

applyIMS

(IMS workflow) whether the filters are only applied to IMS precursors (applyIMS=FALSE), only to IMS features (applyIMS=TRUE) or to both (applyIMS="both"). Other feature groups will always be kept. The negate option does not affect applyIMS.

sets

(sets workflow) A character with name(s) of the sets to keep (or remove if negate=TRUE).

set

(sets workflow) The name of the set.

Value

delete returns the object for which the specified data was removed.

filter returns a filtered featureGroupsScreening object.

Methods (by generic)

  • screenInfo(featureGroupsScreening): Returns a table with screening information (see screenInfo slot).

  • show(featureGroupsScreening): Shows summary information for this object.

  • x[i: Subset on analyses, feature groups and/or suspects.

  • delete(featureGroupsScreening): Completely deletes specified feature groups or screening results.

  • filter(featureGroupsScreening): Performs rule based filtering. This method builds on the comprehensive filter functionality from the base filter,featureGroups-method. It adds several filters to select e.g. the best ranked suspects or those with a minimum estimated identification level. NOTE: most filters only affect suspect hits, not feature groups. Set onlyHits=TRUE to subsequently remove any feature groups that lost any suspect matches due to these filter steps.

Slots

screenInfo

A (data.table) with results from suspect screening. This table will be amended with ID confidence data when estimateIDConfidence is run.

MS2QuantMeta

Metadata from MS2Quant filled in by predictRespFactors.

(sets workflow) A named list with the metadata stored for each set.

Note

filter removes suspect hits with NA values when any of the filters related to minimum or maximum values are applied (unless negate=TRUE).

S4 class hierarchy

  • featureGroups

    • featureGroupsScreening

      • featureGroupsSetScreeningUnset

Sets workflows

The featureGroupsScreeningSet class is applicable for sets workflows. This class is derived from featureGroupsScreening and therefore largely follows the same user interface.

The following methods are specifically defined for sets workflows:

  • unset Converts the object data for a specified set into a 'non-set' object (featureGroupsScreeningUnset), which allows it to be used in 'regular' workflows. Only the screening results present in the specified set are kept.

The following methods are changed or with new functionality:

  • estimateIDConfidence See the Sets workflows section in the documentation for estimateIDConfidence.

  • filter All filters related to estimated identification levels and formula/compound rankings are applied to the overall set data (see above). All others are applied to set specific data: in this case candidates are only removed if none of the set data confirms to the filter.

This class derives also from featureGroupsSet. Please see its documentation for more relevant details with sets workflows.

Note that the formRank and compRank columns are not updated when the data is subset.

See also

featureGroups