spectral_matching {msPurity} | R Documentation

## 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")

[Package msPurity version 1.10.0 Index]