FragPipeAnalystR TMT Global Proteome
Introduction
FragPipeAnalystR is a R package intended for FragPipe downstream analysis. We also make it compatible with the result obtained from FragPipe-Analyst. Users are able to reproduce and customize the plots generated in FragPipe-Analyst.
Quick Start Example
library(FragPipeAnalystR)## ccrcc <- make_se_from_files("/Users/hsiaoyi/Documents/workspace/FragPipeR_manuscript/data/TMT_4plex/abundance_protein_MD.tsv",
"/Users/hsiaoyi/Documents/workspace/FragPipeR_manuscript/data/TMT_4plex/experiment_annotation_clean.tsv",
type = "TMT", level = "protein")plot_pca(ccrcc)
plot_correlation_heatmap(ccrcc)
plot_missval_heatmap(ccrcc)## `use_raster` is automatically set to TRUE for a matrix with more than
## 2000 rows. You can control `use_raster` argument by explicitly setting
## TRUE/FALSE to it.
##
## Set `ht_opt$message = FALSE` to turn off this message.## 'magick' package is suggested to install to give better rasterization.
##
## Set `ht_opt$message = FALSE` to turn off this message.
plot_feature_numbers(ccrcc)
plot_cvs(ccrcc)
You may want to check some of known markers through box plots:
plot_feature(ccrcc, c("Q16790", # CA9
"Q8IVF2", # AHNAK2
"P19404", # NDUFV2
"P01833" # PIGR
))
This could be done via Gene column as well:
plot_feature(ccrcc, c("CA9", "AHNAK2", "NDUFV2", "PIGR"), index="Gene")
de_result <- test_limma(ccrcc, type = "all")## Tested contrasts: Tumor_vs_NATde_result_updated <- add_rejections(de_result)Volcano plot is designed for visualizing differential expression analysis result:
plot_volcano(de_result_updated, "Tumor_vs_NAT")
It could be labelled by different column available in the
rowData(de_result_updated) such as Gene:
plot_volcano(de_result_updated, "Tumor_vs_NAT", name_col="Gene")
or_result <- or_test(de_result_updated, database = "Hallmark", direction = "UP")## Background## Uploading data to Enrichr... Done.
## Querying MSigDB_Hallmark_2020... Done.
## Parsing results... Done.## Tumor_vs_NAT## 773 genes are submitted## Uploading data to Enrichr... Done.
## Querying MSigDB_Hallmark_2020... Done.
## Parsing results... Done.
## Background correction... Done.plot_or(or_result)
or_result <- or_test(de_result_updated, database = "Hallmark", direction = "DOWN")## Background## Uploading data to Enrichr... Done.
## Querying MSigDB_Hallmark_2020... Done.
## Parsing results... Done.## Tumor_vs_NAT## 1432 genes are submitted## Uploading data to Enrichr... Done.
## Querying MSigDB_Hallmark_2020... Done.
## Parsing results... Done.
## Background correction... Done.plot_or(or_result)
sessionInfo()## R version 4.4.1 (2024-06-14)
## Platform: aarch64-apple-darwin20
## Running under: macOS Ventura 13.4
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## time zone: America/Detroit
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices datasets utils methods base
##
## other attached packages:
## [1] FragPipeAnalystR_1.0.1
##
## loaded via a namespace (and not attached):
## [1] RColorBrewer_1.1-3 rstudioapi_0.17.1
## [3] jsonlite_1.8.9 shape_1.4.6.1
## [5] MultiAssayExperiment_1.32.0 magrittr_2.0.3
## [7] ggtangle_0.0.6 farver_2.1.2
## [9] MALDIquant_1.22.3 rmarkdown_2.29
## [11] GlobalOptions_0.1.2 fs_1.6.5
## [13] zlibbioc_1.52.0 vctrs_0.6.5
## [15] memoise_2.0.1 ggtree_3.14.0
## [17] htmltools_0.5.8.1 S4Arrays_1.6.0
## [19] curl_6.2.0 gridGraphics_0.5-1
## [21] SparseArray_1.6.1 mzID_1.44.0
## [23] sass_0.4.9 bslib_0.9.0
## [25] htmlwidgets_1.6.4 plyr_1.8.9
## [27] plotly_4.10.4 impute_1.80.0
## [29] cachem_1.1.0 igraph_2.1.4
## [31] lifecycle_1.0.4 iterators_1.0.14
## [33] pkgconfig_2.0.3 gson_0.1.0
## [35] Matrix_1.7-0 R6_2.5.1
## [37] fastmap_1.2.0 GenomeInfoDbData_1.2.13
## [39] MatrixGenerics_1.18.1 clue_0.3-66
## [41] fdrtool_1.2.18 aplot_0.2.4
## [43] digest_0.6.37 enrichplot_1.26.6
## [45] pcaMethods_1.98.0 colorspace_2.1-1
## [47] patchwork_1.3.0 AnnotationDbi_1.68.0
## [49] S4Vectors_0.44.0 GenomicRanges_1.58.0
## [51] RSQLite_2.3.9 labeling_0.4.3
## [53] cytolib_2.18.2 httr_1.4.7
## [55] abind_1.4-8 compiler_4.4.1
## [57] withr_3.0.2 bit64_4.6.0-1
## [59] doParallel_1.0.17 ConsensusClusterPlus_1.70.0
## [61] BiocParallel_1.40.0 DBI_1.2.3
## [63] ExPosition_2.8.23 R.utils_2.12.3
## [65] MASS_7.3-60.2 prettyGraphs_2.1.6
## [67] DelayedArray_0.32.0 rjson_0.2.23
## [69] mzR_2.40.0 tools_4.4.1
## [71] PSMatch_1.10.0 ape_5.8-1
## [73] R.oo_1.27.0 glue_1.8.0
## [75] nlme_3.1-164 QFeatures_1.16.0
## [77] GOSemSim_2.32.0 grid_4.4.1
## [79] cmapR_1.18.0 cluster_2.1.6
## [81] reshape2_1.4.4 fgsea_1.32.2
## [83] generics_0.1.3 gtable_0.3.6
## [85] tzdb_0.4.0 R.methodsS3_1.8.2
## [87] preprocessCore_1.68.0 tidyr_1.3.1
## [89] hms_1.1.3 data.table_1.16.4
## [91] XVector_0.46.0 BiocGenerics_0.52.0
## [93] ggrepel_0.9.6 foreach_1.5.2
## [95] pillar_1.10.1 stringr_1.5.1
## [97] yulab.utils_0.2.0 limma_3.62.2
## [99] flowCore_2.18.0 circlize_0.4.16
## [101] splines_4.4.1 dplyr_1.1.4
## [103] treeio_1.30.0 lattice_0.22-6
## [105] renv_1.1.0 bit_4.5.0.1
## [107] RProtoBufLib_2.18.0 tidyselect_1.2.1
## [109] GO.db_3.20.0 ComplexHeatmap_2.22.0
## [111] Biostrings_2.74.1 alluvial_0.1-2
## [113] knitr_1.49 IRanges_2.40.1
## [115] ProtGenerics_1.38.0 SummarizedExperiment_1.36.0
## [117] stats4_4.4.1 xfun_0.50
## [119] Biobase_2.66.0 statmod_1.5.0
## [121] MSnbase_2.32.0 matrixStats_1.5.0
## [123] stringi_1.8.4 UCSC.utils_1.2.0
## [125] ggfun_0.1.8 lazyeval_0.2.2
## [127] yaml_2.3.10 evaluate_1.0.3
## [129] codetools_0.2-20 MsCoreUtils_1.18.0
## [131] tibble_3.2.1 qvalue_2.38.0
## [133] BiocManager_1.30.25 ggplotify_0.1.2
## [135] cli_3.6.3 affyio_1.76.0
## [137] munsell_0.5.1 jquerylib_0.1.4
## [139] Rcpp_1.0.14 GenomeInfoDb_1.42.3
## [141] png_0.1-8 XML_3.99-0.18
## [143] parallel_4.4.1 assertthat_0.2.1
## [145] readr_2.1.5 ggplot2_3.5.1
## [147] blob_1.2.4 clusterProfiler_4.14.4
## [149] DOSE_4.0.0 AnnotationFilter_1.30.0
## [151] viridisLite_0.4.2 tidytree_0.4.6
## [153] scales_1.3.0 affy_1.84.0
## [155] ncdf4_1.23 purrr_1.0.2
## [157] crayon_1.5.3 GetoptLong_1.0.5
## [159] rlang_1.1.5 cowplot_1.1.3
## [161] fastmatch_1.1-6 vsn_3.74.0
## [163] KEGGREST_1.46.0 SNFtool_2.3.1