spectral_matching: Spectral matching deprecated

In computational-metabolomics/msPurity: Automated Evaluation of Precursor Ion Purity for Mass Spectrometry Based Fragmentation in Metabolomics

Spectral matching deprecated

Description

Perform spectral matching to spectral libraries using dot product cosine on a LC-MS/MS dataset and link to XCMS features.

msPurity::spectral_matching is deprecated - please use msPurity::spectralMatching for future use

Usage

spectral_matching(
  query_db_pth,
  ra_thres_l = 0,
  ra_thres_q = 2,
  cores = 1,
  pol = "positive",
  ppm_tol_prod = 10,
  ppm_tol_prec = 5,
  score_thres = 0.6,
  topn = NA,
  db_name = NA,
  library_db_pth = NA,
  instrument_types = NA,
  library_sources = "massbank",
  scan_ids = NA,
  pa = NA,
  xset = NA,
  grp_peaklist = NA,
  out_dir = ".",
  ra_w = 0.5,
  mz_w = 2,
  spectra_type_q = "scans",
  ra_thres_t = NA,
  target_db_pth = NA,
  rt_range = c(NA, NA),
  rttol = NA,
  match_alg = "dpc"
)

Arguments

query_db_pth	character; Path of the database of targets (queries) that will be searched against the library spectra. Generated either from frag4feature or from create_database functions.
ra_thres_l	numeric; Relative abundance threshold for library spectra
ra_thres_q	numeric; Relative abundance threshold for target (query) spectra (Peaks below this RA threshold will be excluded)
cores	numeric; Number of cores to use
pol	character; Polarity ['positive' or 'negative']
ppm_tol_prod	numeric; PPM tolerance to match to product
ppm_tol_prec	numeric; PPM tolerance to match to precursor
score_thres	numeric; Dot product cosine score threshold
topn	numeric [optional]; Only use top n matches
db_name	character [optional]; Name of the result database (e.g. can use CAMERA peaklist)
library_db_pth	character [optional]; path to library spectral SQLite database. Defaults to msPurityData package data.
instrument_types	vector [optional]; Vector of instrument types, defaults to all
library_sources	vector [optional]; Vector of library sources. Default option is for massbank only but the 'lipidblast' library is also available
scan_ids	vector [optional]; Vector of unique scan ids calculated from msPurity "pid". These scans will on used for the spectral matching. All scans will be used if set to NA
pa	purityA object [optional]; If target_db_pth set to NA, a new database can be created using pa, xset and grp_peaklist
xset	xcms object [optional]; If target_db_pth set to NA, a new database can be created using pa, xset and grp_peaklist
grp_peaklist	dataframe [optional]; If target_db_pth set to NA, a new database can be created using pa, xset and grp_peaklist
out_dir	character [optional]; If target_db_pth set to NA, Out directory for the SQLite result database
ra_w	numeric; Relative abundance weight for spectra
mz_w	numeric; mz weight for spectra
spectra_type_q	character; Type of fragmentation spectra from query to match with "scans" = all individual scans, "av_intra" = averaged spectra (intra), "av_inter" = averaged spectra (inter), "av_all" = averaged all spectra ignoring inter-intra relationships
ra_thres_t	numeric [deprecated]; The relative abundance threshold for the query spectra (use ra_thres_q for future use)
target_db_pth	character [deprecated]; The query database path (use query_db_pth for future use)
rt_range	vector [optional]; Vector of rention time range to filter the library spectra (rtmin, rtmax). Default is to ignore retention time range
rttol	numeric [optional]; Tolerance in time range between the Library and Query database retention time (in seconds) NA to ignore
match_alg	character; Can either use dot product cosine (dpc) or match factor (mf) for spectral matching. Defaults to dpc

Value

list of database details and dataframe summarising the results for the xcms features

Examples

#msmsPths <- list.files(system.file("extdata", "lcms", "mzML",
#                         package="msPurityData"), full.names = TRUE,
#                         pattern = "MSMS")
#xset <- xcms::xcmsSet(msmsPths)
#xset <- xcms::group(xset)
#xset <- xcms::retcor(xset)
#xset <- xcms::group(xset)

#pa  <- purityA(msmsPths)
#pa <- frag4feature(pa, xset)
#pa <- averageAllFragSpectra(pa)
#db_pth <- create_database(pa, xset)
#q_dbPth <- system.file("extdata", "tests", "db",
#                        "create_database_example.sqlite", package="msPurity")
#result <- spectral_matching(q_dbPth, spectra_type_q="av_all")

computational-metabolomics/msPurity documentation built on April 19, 2022, 10:21 a.m.