MetFragConfig.CompToxCSV: Create MetFrag Config Files with LocalCSV and Scoring Terms...
In schymane/ReSOLUTION: SOLUTIONS for High ReSOLUTION Mass Spectrometry

Description Usage Arguments Details Value Author(s) See Also Examples

This is a CompTox XLS or CSV specific wrapper function for MetFragConfig.

1 2	MetFragConfig.CompToxCSV(mass, adduct_type, results_filename, peaklist_path, base_dir, CompToxLocalCSVterms, ...)

`mass`	The mass with which to search the candidate database (`DB`). Use `neutralPrecursorMass` and `adduct_type` to set whether this is monoisotopic mass or an adduct species. Defaults to `adduct_type`.
`adduct_type`	The adduct species used to define mass (if `neutralPrecursorMass=FALSE`) and fragmentation settings in the config file, entered as either `PrecursorIonType` (text) or `PrecursorIonmode` (a number). The available options are given in the system file `MetFragAdductTypes.csv` in the `extdata` folder. Recommended default values (if ion state is unclear) are `[M+H]+` (1) for positive and `[M-H]-` (-1) for negative mode.
`results_filename`	Enter a base filename for naming the results files - do not include file endings
`peaklist_path`	Enter the full path and file name to the peak list for this config file
`base_dir`	Enter the directory name to set up the subfolders for MetFrag batch results. If the folders don't exist, subfolders `config`, `log` and `results` are created; the output of this function is saved in `config`.
`CompToxLocalCSVterms`	The output of `CompToxXLStoLocalCSVterms`, `CompToxCSVtoLocalCSVterms` or `CompToxFullCSVtoLocalCSVterms`, used to set `DB, localDB_path, UDS_Category and UDS_Weights` in `MetFragConfig`

Remaining parameters are described in MetFragConfig

Returns a MetFrag config file name

Emma Schymanski <emma.schymanski@uni.lu> in partnership with Christoph Ruttkies (MetFragCL), Antony J. Williams and team (CompTox Dashboard)

MetFragConfig, runMetFrag, CompToxXLStoLocalCSVterms, CompToxCSVtoLocalCSVterms, CompToxFullCSVtoLocalCSVterms

# Example from DOI: 10.1021/acs.est.7b01908
# Note that this scores automatically with all metadata fields in the example file, which
# is not necessarily ideal as not all predicted values are relevant for ranking the best candidate.
CompToxXLS <- system.file("extdata","CompToxBatchSearch_MetFrag_MSready_C10H14N2.xls",package="ReSOLUTION")
LocalCSVterms <- CompToxXLStoLocalCSVterms(CompToxXLS)
peaklist <- system.file("extdata","EQ300804_Nicotine_peaks.txt",package="ReSOLUTION")
test_dir <- "C:/DATA/Workflow/MetFrag22/metfrag_test_results"
config_file <- MetFragConfig.CompToxCSV(163.1230, "[M+H]+","Nicotine_PrecMass_MpHp_XLS",peaklist, test_dir, LocalCSVterms)
metfrag_dir <- "C:/DATA/Workflow/MetFrag22/"
MetFragCL_name <- "MetFrag2.4.4-msready-CL.jar"
runMetFrag(config_file, metfrag_dir, MetFragCL_name)

# Example of Simazine
# Note that this uses a CSV file with fewer scoring terms that are more relevant for candidate selection.
CompToxFullCSV_test <- system.file("extdata","dsstox_MS_Ready_MetFragTestCSV5.csv",package="ReSOLUTION")
LocalCSVterms <- CompToxFullCSVtoLocalCSVterms(CompToxFullCSV_test)
peaklist <- system.file("extdata","EA026206_Simazine_peaks.txt",package="ReSOLUTION")
rt_file_path <- system.file("extdata","Eawag_rt_inchi.csv",package="ReSOLUTION")
test_dir <- "C:/DATA/Workflow/MetFrag22/metfrag_test_results"
MBrecord <- system.file("extdata","EA026206_Simazine.txt",package="ReSOLUTION")
MBinfo <- getMBRecordInfo.MetFragConfig(MBrecord,peaklist, writePeaklist=FALSE)
IsPosMode <- grepl(MBinfo$ion_mode,"POSITIVE")
adduct_type <- MBinfo$prec_type
config_file <- MetFragConfig.CompToxCSV(mass=MBinfo$exact_mass,adduct_type = adduct_type,
results_filename = paste0("Simazine", "_byExactMass_5ppm"),peaklist_path = MBinfo$peaklist,neutralPrecursorMass=TRUE,
base_dir = test_dir, CompToxLocalCSVterms = LocalCSVterms, IsPosMode = IsPosMode,rt_file_path = rt_file_path,
rt_exp = MBinfo$ret_time,filter_by_InChIKey = FALSE)

metfrag_dir <- "C:/DATA/Workflow/MetFrag22/"
MetFragCL_name <- "MetFrag2.4.4-msready-CL.jar"
runMetFrag(config_file, metfrag_dir, MetFragCL_name)


# Example of diclofenac
peaklist <- system.file("extdata","EA020161_Diclofenac_peaks.txt",package="ReSOLUTION")
MBrecord <- system.file("extdata","EA020161_Diclofenac.txt",package="ReSOLUTION")
MBinfo <- getMBRecordInfo.MetFragConfig(MBrecord,peaklist, writePeaklist=FALSE)
IsPosMode <- grepl(MBinfo$ion_mode,"POSITIVE")
adduct_type <- MBinfo$prec_type
config_file <- MetFragConfig.CompToxCSV(mass=MBinfo$prec_mass,adduct_type = adduct_type,
results_filename = paste0("Diclofenac", "_byPrecMass_5ppm"),peaklist_path = MBinfo$peaklist,neutralPrecursorMass=FALSE,
base_dir = test_dir, CompToxLocalCSVterms = LocalCSVterms, IsPosMode = IsPosMode,rt_file_path = rt_file_path,
rt_exp = MBinfo$ret_time,filter_by_InChIKey = FALSE)

metfrag_dir <- "C:/DATA/Workflow/MetFrag22/"
MetFragCL_name <- "MetFrag2.4.4-msready-CL.jar"
runMetFrag(config_file, metfrag_dir, MetFragCL_name)