vignettes/other_tools.Rmd
other_tools.RmdThere are also a lot of useful tools in metid.
library(metid)
#> metid 1.2.24 (2022-09-19 17:11:25)
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#> Attaching package: 'metid'
#> The following object is masked from 'package:stats':
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#> filter
library(tidyverse)
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#> ✖ purrr::set_names() masks magrittr::set_names()readMGF
result <- readMGF(file)readMZXML
result <- readMZXML(file, threads = 3)readMGF
result <- readMGF(file)metid version and logo
metid::metid_logo()
#> Thank you for using metid!
#> Version 1.2.24 (2022-09-19 17:11:25)
#> More information: metid.tidymass.org
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sessionInfo()
#> R version 4.2.1 (2022-06-23)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Big Sur ... 10.16
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#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
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#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
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#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
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#> other attached packages:
#> [1] tinytools_0.9.1 forcats_0.5.1.9000 stringr_1.4.0 dplyr_1.0.9
#> [5] purrr_0.3.4 readr_2.1.2 tidyr_1.2.0 tibble_3.1.7
#> [9] tidyverse_1.3.1 ggplot2_3.3.6 massdataset_1.0.5 magrittr_2.0.3
#> [13] masstools_0.99.13 metid_1.2.17
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#> [1] backports_1.4.1 readxl_1.4.0
#> [3] circlize_0.4.15 systemfonts_1.0.4
#> [5] plyr_1.8.7 lazyeval_0.2.2
#> [7] BiocParallel_1.30.3 listenv_0.8.0
#> [9] GenomeInfoDb_1.32.2 Rdisop_1.56.0
#> [11] digest_0.6.29 foreach_1.5.2
#> [13] yulab.utils_0.0.5 htmltools_0.5.2
#> [15] fansi_1.0.3 memoise_2.0.1
#> [17] cluster_2.1.3 doParallel_1.0.17
#> [19] tzdb_0.3.0 openxlsx_4.2.5
#> [21] limma_3.52.2 ComplexHeatmap_2.12.0
#> [23] globals_0.15.1 modelr_0.1.8
#> [25] matrixStats_0.62.0 pkgdown_2.0.5
#> [27] prettyunits_1.1.1 colorspace_2.0-3
#> [29] rvest_1.0.2 haven_2.5.0
#> [31] textshaping_0.3.6 xfun_0.31
#> [33] crayon_1.5.1 RCurl_1.98-1.7
#> [35] jsonlite_1.8.0 impute_1.70.0
#> [37] iterators_1.0.14 glue_1.6.2
#> [39] gtable_0.3.0 zlibbioc_1.42.0
#> [41] XVector_0.36.0 GetoptLong_1.0.5
#> [43] DelayedArray_0.22.0 shape_1.4.6
#> [45] BiocGenerics_0.42.0 scales_1.2.0
#> [47] vsn_3.64.0 DBI_1.1.3
#> [49] Rcpp_1.0.8.3 mzR_2.30.0
#> [51] viridisLite_0.4.0 progress_1.2.2
#> [53] clue_0.3-61 gridGraphics_0.5-1
#> [55] preprocessCore_1.58.0 stats4_4.2.1
#> [57] MsCoreUtils_1.8.0 htmlwidgets_1.5.4
#> [59] httr_1.4.3 RColorBrewer_1.1-3
#> [61] ellipsis_0.3.2 pkgconfig_2.0.3
#> [63] XML_3.99-0.10 dbplyr_2.2.1
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#> [67] ggplotify_0.1.0 tidyselect_1.1.2
#> [69] rlang_1.0.3 munsell_0.5.0
#> [71] cellranger_1.1.0 tools_4.2.1
#> [73] cachem_1.0.6 cli_3.3.0
#> [75] generics_0.1.3 broom_1.0.0
#> [77] evaluate_0.15 fastmap_1.1.0
#> [79] mzID_1.34.0 yaml_2.3.5
#> [81] ragg_1.2.2 knitr_1.39
#> [83] fs_1.5.2 zip_2.2.0
#> [85] ncdf4_1.19 pbapply_1.5-0
#> [87] future_1.26.1 xml2_1.3.3
#> [89] compiler_4.2.1 rstudioapi_0.13
#> [91] plotly_4.10.0 png_0.1-7
#> [93] affyio_1.66.0 reprex_2.0.1
#> [95] bslib_0.3.1 stringi_1.7.6
#> [97] desc_1.4.1 MSnbase_2.22.0
#> [99] lattice_0.20-45 ProtGenerics_1.28.0
#> [101] Matrix_1.4-1 ggsci_2.9
#> [103] vctrs_0.4.1 pillar_1.7.0
#> [105] lifecycle_1.0.1 furrr_0.3.0
#> [107] BiocManager_1.30.18 jquerylib_0.1.4
#> [109] MALDIquant_1.21 GlobalOptions_0.1.2
#> [111] data.table_1.14.2 bitops_1.0-7
#> [113] GenomicRanges_1.48.0 R6_2.5.1
#> [115] pcaMethods_1.88.0 affy_1.74.0
#> [117] IRanges_2.30.0 parallelly_1.32.0
#> [119] codetools_0.2-18 MASS_7.3-57
#> [121] assertthat_0.2.1 SummarizedExperiment_1.26.1
#> [123] rprojroot_2.0.3 rjson_0.2.21
#> [125] withr_2.5.0 S4Vectors_0.34.0
#> [127] GenomeInfoDbData_1.2.8 parallel_4.2.1
#> [129] hms_1.1.1 grid_4.2.1
#> [131] rmarkdown_2.14 MatrixGenerics_1.8.1
#> [133] lubridate_1.8.0 Biobase_2.56.0