Identify metabolites based on MS/MS database.
metIdentify_mass_dataset( object, ms1.match.ppm = 25, ms2.match.ppm = 30, mz.ppm.thr = 400, ms2.match.tol = 0.5, fraction.weight = 0.3, dp.forward.weight = 0.6, dp.reverse.weight = 0.1, rt.match.tol = 30, polarity = c("positive", "negative"), ce = "all", column = c("hilic", "rp"), ms1.match.weight = 0.25, rt.match.weight = 0.25, ms2.match.weight = 0.5, total.score.tol = 0.5, candidate.num = 3, database, threads = 3, remove_fragment_intensity_cutoff = 0 )
A mass_dataset class object.
Precursor match ppm tolerance.
Fragment ion match ppm tolerance.
Accurate mass tolerance for m/z error calculation.
MS2 match (MS2 similarity) tolerance.
The weight for matched fragments.
Forward dot product weight.
Reverse dot product weight.
RT match tolerance.
The polarity of data, "positive"or "negative".
Collision energy. Please confirm the CE values in your database. Default is "all".
"hilic" (HILIC column) or "rp" (reverse phase).
The weight of MS1 match for total score calculation.
The weight of RT match for total score calculation.
The weight of MS2 match for total score calculation.
Total score tolerance. The total score are refering to MS-DIAL.
The number of candidate.
MS2 database name or MS2 database.
Number of threads
default is 0.
A metIdentifyClass object.
The example and demo data of this function can be found https://tidymass.github.io/metid/articles/metid.html