metIdentify_mass_dataset: Metabolite Identification in a mass_dataset Object Using MS1...

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

Metabolite Identification in a mass_dataset Object Using MS1 and MS2 Data

Description

This function identifies potential metabolites in a 'mass_dataset' object by matching MS1 and MS2 data with a reference spectral database. The function uses both MS1 (m/z) and MS2 (fragment ions) matching for more accurate identification.

Usage

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
)

Arguments

object	A 'mass_dataset' object that contains MS1 and MS2 data.
ms1.match.ppm	A numeric value specifying the mass accuracy threshold for MS1 matching in parts per million (ppm). Defaults to '25'.
ms2.match.ppm	A numeric value specifying the mass accuracy threshold for MS2 matching in ppm. Defaults to '30'.
mz.ppm.thr	A numeric value specifying the m/z threshold in ppm for matching MS1 and MS2. Defaults to '400'.
ms2.match.tol	A numeric value specifying the tolerance for MS2 fragment ion matching. Defaults to '0.5'.
fraction.weight	A numeric value specifying the weight for the MS2 fragmentation score. Defaults to '0.3'.
dp.forward.weight	A numeric value specifying the weight for the forward dot product in MS2 matching. Defaults to '0.6'.
dp.reverse.weight	A numeric value specifying the weight for the reverse dot product in MS2 matching. Defaults to '0.1'.
rt.match.tol	A numeric value specifying the retention time matching tolerance in seconds. Defaults to '30'.
polarity	A character string specifying the ionization mode. It can be either '"positive"' or '"negative"'. Defaults to '"positive"'.
ce	A character string specifying the collision energy for MS2 matching. Defaults to '"all"'.
column	A character string specifying the chromatographic column type, either '"hilic"' (hydrophilic interaction) or '"rp"' (reverse phase). Defaults to '"hilic"'.
ms1.match.weight	A numeric value specifying the weight of MS1 matching in the total score calculation. Defaults to '0.25'.
rt.match.weight	A numeric value specifying the weight of RT matching in the total score calculation. Defaults to '0.25'.
ms2.match.weight	A numeric value specifying the weight of MS2 matching in the total score calculation. Defaults to '0.5'.
total.score.tol	A numeric value specifying the threshold for the total score. Defaults to '0.5'.
candidate.num	A numeric value specifying the number of top candidates to retain per feature. Defaults to '3'.
database	A 'databaseClass' object containing the reference spectral database for annotation.
threads	An integer specifying the number of threads to use for parallel processing. Defaults to '3'.
remove_fragment_intensity_cutoff	A numeric value specifying the intensity cutoff for removing fragments in MS2 matching. Defaults to '0'.

Details

This function performs MS1 and MS2-based matching between the experimental data in the 'mass_dataset' object and a reference spectral database. The matching process is based on mass-to-charge ratio (m/z), retention time (RT), and MS2 fragmentation patterns. The function supports both positive and negative ionization modes and can work with either HILIC or reverse-phase columns.

The matching process can be fine-tuned by adjusting the weights of MS1, MS2, and RT matching, as well as the tolerance parameters for m/z and MS2 matching.

Value

A data frame containing the metabolite identification results, including m/z error, RT error, MS2 matching scores, and information about the identified compounds.

Author(s)

Xiaotao Shen [e-mail]

Examples

## Not run: 
# Perform MS1 and MS2-based metabolite identification in a mass_dataset object
identification_result <- metIdentify_mass_dataset(
  object = mass_object,
  ms1.match.ppm = 20,
  ms2.match.ppm = 25,
  rt.match.tol = 20,
  database = reference_database,
  threads = 4
)

## End(Not run)

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