getAnnotation: Annotate adducts and fragments

In cliqueMS: Annotation of Isotopes, Adducts and Fragmentation Adducts for in-Source LC/MS Metabolomics Data

Description

This function annotates adducts after isotope annotation. For each clique group, it searches for combinations of two or more features compatible with the same neutral mass and two or more adducts in 'adinfo' list. For clique groups than have more than one annotation solution, it scores all possibilities and returns the top five solutions.

Usage

getAnnotation(anclique, adinfo, polarity, topmasstotal = 10,
    topmassf = 1, sizeanG = 20, ppm = 10, filter = 1e-04,
    emptyS = -6, normalizeScore = TRUE)

Arguments

anclique	Object of class 'anClique' with isotope annotation
adinfo	data.frame with columns 'adduct' with adduct name, column 'log10freq' with the log10 frequency of each adduct in the list, column 'massdiff' with the adduct mass diff, column 'nummol' with the number of metabolite's molecule necessary for that adduct and column 'charge' with the charge of that adduct.
polarity	Polarity of the adducts, choose between 'positive' or 'negative'
topmasstotal	All neutral masses in the group are ordered based on their adduct log-frequencies and their number of adducts. From that list, a number of "topmasstotal" masses are selected for the final annotation.
topmassf	In addition to 'topmasstotal', for each feature the list of ordered neutral masses is subsetted to the masses with an adduct in that particular feature. For each sublist, a number 'topmassf' neutral masses are also selected for the final annotation.
sizeanG	After neutral mass selection, if a clique group has a number of monoisotopic features bigger than 'sizeanG', the annotation group is divided into non-overlapping annotation groups. Each subdivision is annotated independently.
ppm	Relative error in ppm in which we consider two or more features compatible with a neutral mass and two or more adducts in 'adinfo'.
filter	This parameter removes redundant annotations. If two neutral masses in the same annotation group have a relative mass difference smaller than 'filter' and the same features and adducts, drop the neutral mass with less adducts
emptyS	Score given to non annotated features. If you use your own 'adinfo', do not set 'emptyS' bigger than any adduct log frequency in your list.
normalizeScore	If 'TRUE', the reported score is normalized and scaled. Normalized score goes from 0, when it means that the raw score is close to the minimum score (all features with empty annotations), up to 100, which is the score value of the theoretical maximum annotation (all the adducts of the list with the minimum number of neutral masses).

Details

The default 'adinfo' lists are 'positive.adinfo' and 'negative.adinfo'. For use load them with 'data(positive.adinfo)' or data(negative.adinfo) commands. Reported scores do not always refer to the entire clique group. There might be features whose annotation is independent from other features of the clique group. This occurs when there are no neutral masses with adducts in both groups of features. Therefore, the clique group is divided in non overlapping regions, called annotation groups. Scores report for these annotation groups. To compare scores between different groups use 'normalizeScore' = TRUE.

If clique groups have a lot of features, there are many combinations of neutral masses and adducts. This could lead to long running times to score the top annotations. Parameters 'topmassf' and 'topmasstotal' are relevant in those cases to drop the less likely neutral masses to speed up the time of computation and still obtain the most plausible annotation. If the clique group is small usually no neutral masses are discarded for the scoring.

Value

An 'anClique' object with annotation columns added to the peaklist

Examples

data(ex.cliqueGroups)
show(ex.cliqueGroups)
ex.isoAn <- getIsotopes(ex.cliqueGroups)
show(ex.isoAn)
data(positive.adinfo)
ex.adductAn <- getAnnotation(ex.isoAn, positive.adinfo, 'positive')

cliqueMS documentation built on Nov. 8, 2020, 7:36 p.m.