eic.qual: Internal function: Calculate the single predictor quality.

In yufree/apLCMS: Adaptive processing of LC-MS data

Description

For each column of an EIC data feature matrix, find its predictive power on the m/z match to known metabolites.

Usage

eic.qual(eic.rec, known.mz, mass.matched = NA, match.tol.ppm = 5, do.plot = FALSE, pos.confidence = 0.99, neg.confidence = 0.99)

Arguments

eic.rec	The EIC data feature matrix. Each row is an EIC. Each column is a data feature.
known.mz	The known m/z values to be matched to.
mass.matched	A vector of indicators of whether the m/z of each EIC is matched to the known m/z values. The default is NA, in which case it is calculated within the function.
match.tol.ppm	The tolerance level of m/z match.
do.plot	Whether to produce plots of the ROCS.
pos.confidence	The confidence level for the features matched to the known feature list.
neg.confidence	The confidence level for the features not matching to the known feature list.

Value

A matrix of four columns. The first two columns are the VUS and AUC without uncertainty. The next two columns are the VUS and AUC with uncertainty.

Author(s)

Tianwei Yu <[e-mail]>

References

Bioinformatics. 30(20): 2941-2948.

yufree/apLCMS documentation built on Jan. 11, 2020, 8:18 p.m.