identify_metabolites_params: Generate the parameter list for identify_metabolites function

In tidymass/metid: Metabolite identification based on MS1 and MS2 spectra

Generate the parameter list for identify_metabolites function

Description

Generate the parameter list for metIdentify function.

Usage

identify_metabolites_params(
  ms1.ms2.match.mz.tol = 25,
  ms1.ms2.match.rt.tol = 10,
  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
)

Arguments

ms1.ms2.match.mz.tol	MS1 peak and MS2 spectrum matching m/z tolerance. Default is 25 pm.
ms1.ms2.match.rt.tol	MS1 peak and MS2 spectrum matching RT tolerance. Default is 10 s.
ms1.match.ppm	Precursor match ppm tolerance.
ms2.match.ppm	Fragment ion match ppm tolerance.
mz.ppm.thr	Accurate mass tolerance for m/z error calculation.
ms2.match.tol	MS2 match (MS2 similarity) tolerance.
fraction.weight	The weight for matched fragments.
dp.forward.weight	Forward dot product weight.
dp.reverse.weight	Reverse dot product weight.
rt.match.tol	RT match tolerance.
polarity	The polarity of data, "positive"or "negative".
ce	Collision energy. Please confirm the CE values in your database. Default is "all".
column	"hilic" (HILIC column) or "rp" (reverse phase).
ms1.match.weight	The weight of MS1 match for total score calculation.
rt.match.weight	The weight of RT match for total score calculation.
ms2.match.weight	The weight of MS2 match for total score calculation.
total.score.tol	Total score tolerance. The total score are refering to MS-DIAL.
candidate.num	The number of candidate.
database	MS2 database name or MS2 database.
threads	Number of threads

Value

A metIdentifyClass object.

Author(s)

Xiaotao Shen [e-mail]

See Also

The example and demo data of this function can be found https://tidymass.github.io/metid/articles/multiple_databases.html

Examples

 param1 <-
identify_metabolites_params(
  ms1.match.ppm = 15,
  rt.match.tol = 15,
  polarity = "positive",
  ce = "all",
  column = "rp",
  total.score.tol = 0.5,
  candidate.num = 3,
  threads = 3,
  database = "msDatabase_rplc0.0.2"
)
param1

tidymass/metid documentation built on Oct. 8, 2024, 10:32 p.m.