View source: R/deprecated_metIdentify4all.R
metIdentify4all | R Documentation |
Identify metabolites using multiple databases one time. \lifecyclematuring
metIdentify4all(ms1.data, ms2.data, parameter.list, path = ".")
ms1.data |
The name of ms1 peak table (csv format). Column 1 is "name", column 2 is "mz" and column 3 is "rt" (second). |
ms2.data |
MS2 data, must be mgf, msp or mzXML format. For example, ms2.data = c("test.mgf", "test2.msp"). |
parameter.list |
A list contains paramters for each processing. The parameter must get using metIdentifyParam or mzIdentifyParam. |
path |
Work directory. |
A list containing mzIdentifyClass object.
Xiaotao Shen shenxt1990@163.com
The example and demo data of this function can be found https://jaspershen.github.io/metID/articles/multiple_databases.html
## Not run: ##creat a folder nameed as example path <- file.path(".", "example") dir.create(path = path, showWarnings = FALSE) ##get MS1 peak table from metID ms1_peak <- system.file("ms1_peak", package = "metID") file.copy( from = file.path(ms1_peak, "ms1.peak.table.csv"), to = path, overwrite = TRUE, recursive = TRUE ) ##get MS2 data from metID ms2_data <- system.file("ms2_data", package = "metID") file.copy( from = file.path(ms2_data, "QC1_MSMS_NCE25.mgf"), to = path, overwrite = TRUE, recursive = TRUE ) ##get databases from metID database <- system.file("ms2_database", package = "metID") file.copy( from = file.path( database, c( "msDatabase_rplc0.0.2", "orbitrapDatabase0.0.1", "hmdbMS1Database0.0.1" ) ), to = path, overwrite = TRUE, recursive = TRUE ) 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" ) param2 <- 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 = "orbitrapDatabase0.0.1" ) param3 <- 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 = "hmdbMS1Database0.0.1" ) result <- metIdentify4all( ms1.data = "ms1.peak.table.csv", ms2.data = "QC1_MSMS_NCE25.mgf", parameter.list = c(param1, param2, param3), path = path ) result[[1]] result[[2]] result[[3]] ## End(Not run)
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