objective: Weight Parameter Objective Function
In metabCombiner: Method for Combining LC-MS Metabolomics Feature Measurements

Description Usage Arguments Details Value

This function evaluates the A, B, C weight parameters in terms of score separability of matching versus mismatching compound alignments. Higher objective function value imply a superior weight parameter selection.

objective(
  cTable,
  idtable,
  A,
  B,
  C,
  minScore,
  mzdiff,
  rtdiff,
  qdiff,
  rtrange,
  adductdiff,
  penalty,
  matches,
  mismatches
)

`cTable`	data frame. Abridged `metabCombiner` report table.
`idtable`	data frame containing all evaluated identities
`A`	Numeric weight for penalizing m/z differences.
`B`	Numeric weight for penalizing differences between fitted & observed retention times
`C`	Numeric weight for differences in Q (abundance quantiles).
`minScore`	numeric. Minimum score to count towards objective value.
`mzdiff`	numeric differences between feature m/z values
`rtdiff`	Differences between model-projected retention time value & observed retention time
`qdiff`	Difference between feature quantile Q values.
`rtrange`	range of dataset Y retention times
`adductdiff`	Numeric divisors of computed score when non-empty adduct labels do not match
`penalty`	positive numeric penalty wherever S(i,j) > S(i,i), i =/= j
`matches`	integer row indices of identity matches
`mismatches`	list of integer identity row mismatches for each identity

First, the similarity scores between all grouped features are calculated as described in scorePairs

Then, the objective value for a similarity S is evaluated as:

OBJ(S) = ∑ h(S(i,i)) - h(S(i, j)) - p(S(i,i) > S(i,j))

-S(i,i) represents the similarity between correct identity alignments
-S(i,j), represents the maximum similarity of i to grouped feature j, i =/= j (the highest-scoring misalignment)
-h(x) = x if x > minScore, 0 otherwise
-p(COND) = 0 if the condition is true, and a penalty value otherwise

This is summed over all labeled compound identities (e.g. idx = idy) shared between input datasets.

A numeric value quantifying total separability of compound match similarity scores from mismatch scores, given A,B,C values

metabCombiner documentation built on Dec. 10, 2020, 2 a.m.