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

 objective R Documentation

## Weight Parameter Objective Function

### Description

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.

### Usage

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

### Arguments

 `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

### Details

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.

### Value

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

hhabra/metabCombiner documentation built on Sept. 13, 2022, 6:25 a.m.