vignettes/Version0_9_2.Rmd
Version0_9_2.RmdIn version 0.9.2, I just modified the
database argument in identify_metabolites()
and identify_metabolite_alls functions. Now you can put the
database in the work directory and then give the database name, and you
can also directory provide the database (databaseClass) to
it.
First we load the MS1 peak and database from metid
package and then put them in a example folder.
##create a folder named 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)
#> [1] TRUE
##get database from metid
database <- system.file("ms2_database", package = "metid")
file.copy(from = file.path(database, "msDatabase_rplc0.0.2"),
to = path, overwrite = TRUE, recursive = TRUE)
#> [1] TRUENow in your ./example, there are two files, namely
ms1.peak.table.csv and msDatabase_rplc_0.0.2,
respectively.
annotate_result1 <-
identify_metabolites(ms1.data = "ms1.peak.table.csv",
ms1.match.ppm = 15,
rt.match.tol = 1000000,
polarity = "positive",
column = "rp",
path = path,
candidate.num = 3,
database = "msDatabase_rplc0.0.2",
threads = 5)
#>
[33mYou don't provide MS2 data, so only use mz and/or RT for matching.
#>
[39m
[33mYou set rt.match.tol > 10,000, so RT will not be used for matching.
#>
[39m
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#>
#>
[41mAll done.
#>
[49m
msDatabase_rplc0.0.2
#> -----------Base information------------
#> Version: 0.0.2
#> Source: MS
#> Link: http://snyderlab.stanford.edu/
#> Creater: Xiaotao Shen ( shenxt1990@163.com )
#> With RT information
#> -----------Spectral information------------
#> There are 14 items of metabolites in database:
#> Lab.ID; Compound.name; mz; RT; CAS.ID; HMDB.ID; KEGG.ID; Formula; mz.pos; mz.neg; Submitter; Family; Sub.pathway; Note
#> There are 833 metabolites in total
#> There are 356 metabolites in positive mode with MS2 spectra.
#> There are 534 metabolites in negative mode with MS2 spectra.
#> Collision energy in positive mode (number:):
#> Total number: 2
#> NCE25; NCE50
#> Collision energy in negative mode:
#> Total number: 2
#> NCE25; NCE50
#> Then we can directory provide this database to
identify_metabolites():
annotate_result2 <-
identify_metabolites(ms1.data = "ms1.peak.table.csv",
ms1.match.ppm = 15,
rt.match.tol = 1000000,
polarity = "positive",
column = "rp",
path = path,
candidate.num = 3,
database = msDatabase_rplc0.0.2,
threads = 5)
#>
[33mYou don't provide MS2 data, so only use mz and/or RT for matching.
#>
[39m
[33mYou set rt.match.tol > 10,000, so RT will not be used for matching.
#>
[39m
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#>
#>
[41mAll done.
#>
[49mBut what should be noticed is that it have different name for database in the final result:
annotate_result1@database
#> [1] "msDatabase_rplc0.0.2"
annotate_result2@database
#> [1] "MS_0.0.2"It is because that if you give the
databaseClass, soidentify_metabolitescan know the name of database, if just use thesourceandversionas the name for database.
paste(msDatabase_rplc0.0.2@database.info$Source,
msDatabase_rplc0.0.2@database.info$Version,
sep = "_")
#> [1] "MS_0.0.2"
sessionInfo()
#> R version 4.1.2 (2021-11-01)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Big Sur 10.16
#>
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
#>
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] tinytools_0.9.1 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.8
#> [5] purrr_0.3.4 readr_2.1.2 tidyr_1.2.0 tibble_3.1.6
#> [9] ggplot2_3.3.5 tidyverse_1.3.1 massdataset_0.99.7 magrittr_2.0.2
#> [13] masstools_0.99.3 metid_1.2.2
#>
#> loaded via a namespace (and not attached):
#> [1] readxl_1.3.1 backports_1.4.1 circlize_0.4.14
#> [4] systemfonts_1.0.3 plyr_1.8.6 lazyeval_0.2.2
#> [7] BiocParallel_1.28.3 crosstalk_1.2.0 listenv_0.8.0
#> [10] leaflet_2.1.0 digest_0.6.29 foreach_1.5.2
#> [13] yulab.utils_0.0.4 htmltools_0.5.2 fansi_1.0.2
#> [16] memoise_2.0.1 cluster_2.1.2 doParallel_1.0.17
#> [19] tzdb_0.2.0 openxlsx_4.2.5 limma_3.50.0
#> [22] ComplexHeatmap_2.10.0 globals_0.14.0 modelr_0.1.8
#> [25] matrixStats_0.61.0 vroom_1.5.7 pkgdown_2.0.2
#> [28] colorspace_2.0-2 rvest_1.0.2 textshaping_0.3.6
#> [31] haven_2.4.3 xfun_0.29 crayon_1.5.0
#> [34] jsonlite_1.7.3 impute_1.68.0 iterators_1.0.14
#> [37] glue_1.6.1 gtable_0.3.0 zlibbioc_1.40.0
#> [40] GetoptLong_1.0.5 shape_1.4.6 BiocGenerics_0.40.0
#> [43] scales_1.1.1 vsn_3.62.0 DBI_1.1.2
#> [46] Rcpp_1.0.8 mzR_2.28.0 viridisLite_0.4.0
#> [49] clue_0.3-60 gridGraphics_0.5-1 bit_4.0.4
#> [52] preprocessCore_1.56.0 stats4_4.1.2 MsCoreUtils_1.6.0
#> [55] htmlwidgets_1.5.4 httr_1.4.2 RColorBrewer_1.1-2
#> [58] ellipsis_0.3.2 pkgconfig_2.0.3 XML_3.99-0.8
#> [61] sass_0.4.0 dbplyr_2.1.1 utf8_1.2.2
#> [64] ggplotify_0.1.0 tidyselect_1.1.1 rlang_1.0.1
#> [67] munsell_0.5.0 cellranger_1.1.0 tools_4.1.2
#> [70] cachem_1.0.6 cli_3.2.0 generics_0.1.2
#> [73] broom_0.7.12 evaluate_0.15 fastmap_1.1.0
#> [76] mzID_1.32.0 yaml_2.3.4 ragg_1.2.1
#> [79] bit64_4.0.5 knitr_1.37 fs_1.5.2
#> [82] zip_2.2.0 ncdf4_1.19 pbapply_1.5-0
#> [85] future_1.23.0 xml2_1.3.3 compiler_4.1.2
#> [88] rstudioapi_0.13 plotly_4.10.0 png_0.1-7
#> [91] affyio_1.64.0 reprex_2.0.1 bslib_0.3.1
#> [94] stringi_1.7.6 desc_1.4.0 MSnbase_2.20.4
#> [97] lattice_0.20-45 ProtGenerics_1.26.0 ggsci_2.9
#> [100] vctrs_0.3.8 pillar_1.7.0 lifecycle_1.0.1
#> [103] furrr_0.2.3 BiocManager_1.30.16 jquerylib_0.1.4
#> [106] MALDIquant_1.21 GlobalOptions_0.1.2 data.table_1.14.2
#> [109] R6_2.5.1 pcaMethods_1.86.0 affy_1.72.0
#> [112] IRanges_2.28.0 parallelly_1.30.0 codetools_0.2-18
#> [115] MASS_7.3-55 assertthat_0.2.1 rprojroot_2.0.2
#> [118] rjson_0.2.21 withr_2.4.3 S4Vectors_0.32.3
#> [121] parallel_4.1.2 hms_1.1.1 grid_4.1.2
#> [124] rmarkdown_2.11 Biobase_2.54.0 lubridate_1.8.0