Examples
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-[{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"installation","dir":"Articles","previous_headings":"","what":"Installation","title":"MSstatsBioNet Introduction","text":"Run code install MSstatsBioNet bioconductor","code":"if (!require(\"BiocManager\", quietly = TRUE)) { install.packages(\"BiocManager\") } BiocManager::install(\"MSstatsBioNet\")"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"purpose-of-msstatsbionet","dir":"Articles","previous_headings":"","what":"Purpose of MSstatsBioNet","title":"MSstatsBioNet Introduction","text":"MSstatsBioNet package member MSstats family packages. contains set functions interpretation mass spectrometry (MS) statistical analysis results context protein-protein interaction networks. package designed used conjunction MSstats package.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"msstats-convert-from-upstream-dataset","dir":"Articles","previous_headings":"","what":"MSstats Convert from Upstream Dataset","title":"MSstatsBioNet Introduction","text":"first convert input data format can processed MSstats. example, MetamorpheusToMSstatsFormat function used convert input data Metamorpheus MSstats format. MSstats format contain necessary information downstream analysis, peptide information, abundance values, run ID, experimental annotation information.","code":"library(MSstatsConvert) input <- system.file(\"tinytest/raw_data/Metamorpheus/AllQuantifiedPeaks.tsv\", package = \"MSstatsConvert\" ) input <- data.table::fread(input) annot <- system.file(\"tinytest/raw_data/Metamorpheus/Annotation.tsv\", package = \"MSstatsConvert\" ) annot <- data.table::fread(annot) msstats_imported <- MetamorpheusToMSstatsFormat(input, annotation = annot, use_log_file = FALSE ) #> INFO [2024-10-31 16:27:26] ** Raw data from Metamorpheus imported successfully. #> INFO [2024-10-31 16:27:26] ** Raw data from Metamorpheus cleaned successfully. #> INFO [2024-10-31 16:27:26] ** Using provided annotation. #> INFO [2024-10-31 16:27:26] ** Run labels were standardized to remove symbols such as '.' or '%'. #> INFO [2024-10-31 16:27:26] ** The following options are used: #> - Features will be defined by the columns: PeptideSequence, PrecursorCharge #> - Shared peptides will be removed. #> - Proteins with single feature will not be removed. #> - Features with less than 3 measurements across runs will be removed. #> INFO [2024-10-31 16:27:26] ** Features with all missing measurements across runs are removed. #> INFO [2024-10-31 16:27:26] ** Shared peptides are removed. #> INFO [2024-10-31 16:27:26] ** Multiple measurements in a feature and a run are summarized by summaryforMultipleRows: max #> INFO [2024-10-31 16:27:26] ** Features with one or two measurements across runs are removed. #> INFO [2024-10-31 16:27:26] ** Run annotation merged with quantification data. #> INFO [2024-10-31 16:27:26] ** Features with one or two measurements across runs are removed. #> INFO [2024-10-31 16:27:26] ** Fractionation handled. #> INFO [2024-10-31 16:27:26] ** Updated quantification data to make balanced design. Missing values are marked by NA #> INFO [2024-10-31 16:27:26] ** Finished preprocessing. The dataset is ready to be processed by the dataProcess function. head(msstats_imported) #> ProteinName PeptideSequence #> 1 O43707 AC[Common Fixed:Carbamidomethyl on C]LISLGYDVENDRQGEAEFNR #> 2 O43707 AC[Common Fixed:Carbamidomethyl on C]LISLGYDVENDRQGEAEFNR #> 3 O43707 AC[Common Fixed:Carbamidomethyl on C]LISLGYDVENDRQGEAEFNR #> 4 O43707 AC[Common Fixed:Carbamidomethyl on C]LISLGYDVENDRQGEAEFNR #> 5 B9A064 AGVETTKPSK #> 6 B9A064 AGVETTKPSK #> PrecursorCharge FragmentIon ProductCharge IsotopeLabelType Condition #> 1 3 NA NA L neg #> 2 3 NA NA L neg #> 3 3 NA NA L pos #> 4 3 NA NA L pos #> 5 2 NA NA L neg #> 6 2 NA NA L neg #> BioReplicate Run Fraction Intensity #> 1 1 NEG1-calib 1 NA #> 2 2 NEG2-calib 1 655481.2 #> 3 3 POS1-calib 1 496891.9 #> 4 4 POS2-calib 1 213691.0 #> 5 1 NEG1-calib 1 4201663.3 #> 6 2 NEG2-calib 1 4427577.4"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"msstats-process-and-groupcomparison","dir":"Articles","previous_headings":"","what":"MSstats Process and GroupComparison","title":"MSstatsBioNet Introduction","text":"Next, preprocess data using dataProcess function perform statistical analysis using groupComparison function. output groupComparison table containing list differentially abundant proteins associated p-values log fold changes.","code":"library(MSstats) #> #> Attaching package: 'MSstats' #> The following objects are masked from 'package:MSstatsConvert': #> #> DIANNtoMSstatsFormat, DIAUmpiretoMSstatsFormat, #> FragPipetoMSstatsFormat, MaxQtoMSstatsFormat, #> OpenMStoMSstatsFormat, OpenSWATHtoMSstatsFormat, PDtoMSstatsFormat, #> ProgenesistoMSstatsFormat, SkylinetoMSstatsFormat, #> SpectronauttoMSstatsFormat #> The following object is masked from 'package:grDevices': #> #> savePlot QuantData <- dataProcess(msstats_imported, use_log_file = FALSE) #> INFO [2024-10-31 16:27:27] ** Log2 intensities under cutoff = 16.018 were considered as censored missing values. #> INFO [2024-10-31 16:27:27] ** Log2 intensities = NA were considered as censored missing values. #> INFO [2024-10-31 16:27:27] ** Use all features that the dataset originally has. #> INFO [2024-10-31 16:27:27] #> # proteins: 7 #> # peptides per protein: 1-26 #> # features per peptide: 1-1 #> INFO [2024-10-31 16:27:27] Some proteins have only one feature: #> O00391 ... #> INFO [2024-10-31 16:27:27] #> neg pos #> # runs 2 2 #> # bioreplicates 2 2 #> # tech. replicates 1 1 #> INFO [2024-10-31 16:27:27] == Start the summarization per subplot... #> | | | 0% | |========== | 14% | |==================== | 29% | |============================== | 43% | |======================================== | 57% | |================================================== | 71% | |============================================================ | 86% | |======================================================================| 100% #> INFO [2024-10-31 16:27:27] == Summarization is done. groupComparisonResult <- groupComparison( contrast.matrix = \"pairwise\", data = QuantData, use_log_file = FALSE ) #> INFO [2024-10-31 16:27:27] == Start to test and get inference in whole plot ... #> | | | 0% | |========== | 14% | |==================== | 29% | |============================== | 43% | |======================================== | 57% | |================================================== | 71% | |============================================================ | 86% | |======================================================================| 100% #> INFO [2024-10-31 16:27:27] == Comparisons for all proteins are done."},{"path":[]},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"id-conversion","dir":"Articles","previous_headings":"MSstatsBioNet Analysis","what":"ID Conversion","title":"MSstatsBioNet Introduction","text":"First, need convert group comparison results format can processed INDRA. getSubnetworkFromIndra function requires table containing HGNC IDs. can use following mapping convert Uniprot HGNC ID. mapping obtained Python uniprot client future, uniprot client added separate function allow users perform conversion R streamlined way.","code":"library(MSstatsBioNet) uniprot_to_hgnc_mapping <- c( \"B9A064\" = \"38476\", \"O00391\" = \"9756\", \"O14818\" = \"9536\", \"O43598\" = \"21218\", \"O43707\" = \"166\", \"P16050\" = \"11390\", \"P84243\" = \"4765\" ) groupComparisonResult$ComparisonResult$HgncId <- uniprot_to_hgnc_mapping[ groupComparisonResult$ComparisonResult$Protein ]"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"subnetwork-query","dir":"Articles","previous_headings":"MSstatsBioNet Analysis","what":"Subnetwork Query","title":"MSstatsBioNet Introduction","text":"package provides function getSubnetworkFromIndra retrieves subnetwork proteins INDRA database based differential abundance analysis results. package distributed Artistic-2.0 license. However, dependencies may different licenses. example, getSubnetworkFromIndra depends INDRA, distributed BSD 2-Clause license. Furthermore, INDRA’s knowledge sources may different licenses commercial applications. Please refer INDRA README information knowledge sources associated licenses.","code":"subnetwork <- getSubnetworkFromIndra(groupComparisonResult$ComparisonResult) #> Warning in getSubnetworkFromIndra(groupComparisonResult$ComparisonResult): NOTICE: This function includes third-party software components #> that are licensed under the BSD 2-Clause License. Please ensure to #> include the third-party licensing agreements if redistributing this #> package or utilizing the results based on this package. #> See the LICENSE file for more details."},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"visualize-networks","dir":"Articles","previous_headings":"MSstatsBioNet Analysis","what":"Visualize Networks","title":"MSstatsBioNet Introduction","text":"function visualizeNetworks takes output getSubnetworkFromIndra visualizes subnetwork. function requires Cytoscape desktop open visualization work. network diagram displayed Cytoscape, see two arrows connecting two nodes, P16050 P84243. arrows represent interactions two proteins, notably activation phosphorylation.","code":"visualizeNetworks(subnetwork$nodes, subnetwork$edges) #> Warning in visualizeNetworks(subnetwork$nodes, subnetwork$edges): Visualization #> is not available in non-interactive mode."},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"session-info","dir":"Articles","previous_headings":"","what":"Session info","title":"MSstatsBioNet Introduction","text":"","code":"sessionInfo() #> R version 4.4.1 (2024-06-14) #> Platform: x86_64-pc-linux-gnu #> Running under: Ubuntu 22.04.5 LTS #> #> Matrix products: default #> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 #> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0 #> #> locale: #> [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8 #> [4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8 #> [7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C #> [10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C #> #> time zone: UTC #> tzcode source: system (glibc) #> #> attached base packages: #> [1] stats graphics grDevices utils datasets methods base #> #> other attached packages: #> [1] MSstatsBioNet_0.99.5 MSstats_4.14.0 MSstatsConvert_1.16.0 #> [4] BiocStyle_2.34.0 #> #> loaded via a namespace (and not attached): #> [1] tidyselect_1.2.1 viridisLite_0.4.2 IRdisplay_1.1 #> [4] dplyr_1.1.4 bitops_1.0-9 RCurl_1.98-1.16 #> [7] fastmap_1.2.0 lazyeval_0.2.2 base64url_1.4 #> [10] XML_3.99-0.17 digest_0.6.37 lifecycle_1.0.4 #> [13] survival_3.6-4 statmod_1.5.0 r2r_0.1.1 #> [16] magrittr_2.0.3 compiler_4.4.1 rlang_1.1.4 #> [19] sass_0.4.9 tools_4.4.1 utf8_1.2.4 #> [22] yaml_2.3.10 data.table_1.16.2 knitr_1.48 #> [25] htmlwidgets_1.6.4 curl_5.2.3 marray_1.84.0 #> [28] RColorBrewer_1.1-3 repr_1.1.7 KernSmooth_2.23-24 #> [31] pbdZMQ_0.3-13 purrr_1.0.2 BiocGenerics_0.52.0 #> [34] desc_1.4.3 stats4_4.4.1 grid_4.4.1 #> [37] preprocessCore_1.68.0 fansi_1.0.6 caTools_1.18.3 #> [40] colorspace_2.1-1 log4r_0.4.4 ggplot2_3.5.1 #> [43] scales_1.3.0 gtools_3.9.5 MASS_7.3-60.2 #> [46] cli_3.6.3 rmarkdown_2.28 crayon_1.5.3 #> [49] ragg_1.3.3 generics_0.1.3 httr_1.4.7 #> [52] minqa_1.2.8 cachem_1.1.0 splines_4.4.1 #> [55] parallel_4.4.1 BiocManager_1.30.25 base64enc_0.1-3 #> [58] vctrs_0.6.5 boot_1.3-30 Matrix_1.7-0 #> [61] jsonlite_1.8.9 bookdown_0.41 ggrepel_0.9.6 #> [64] systemfonts_1.1.0 limma_3.62.0 plotly_4.10.4 #> [67] jquerylib_0.1.4 tidyr_1.3.1 glue_1.8.0 #> [70] nloptr_2.1.1 pkgdown_2.1.1 RJSONIO_1.3-1.9 #> [73] stringi_1.8.4 gtable_0.3.6 lme4_1.1-35.5 #> [76] munsell_0.5.1 tibble_3.2.1 pillar_1.9.0 #> [79] htmltools_0.5.8.1 gplots_3.2.0 RCy3_2.26.0 #> [82] graph_1.84.0 IRkernel_1.3.2 R6_2.5.1 #> [85] textshaping_0.4.0 evaluate_1.0.1 lattice_0.22-6 #> [88] backports_1.5.0 bslib_0.8.0 Rcpp_1.0.13 #> [91] uuid_1.2-1 nlme_3.1-164 checkmate_2.3.2 #> [94] xfun_0.48 fs_1.6.5 pkgconfig_2.0.3"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Anthony Wu. Author, maintainer. Olga Vitek. Author.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Wu , Vitek O (2024). MSstatsBioNet: Network Analysis MS-based Proteomics Experiments. R package version 0.99.5, https://vitek-lab.github.io/MSstatsBioNet/, http://msstats.org.","code":"@Manual{, title = {MSstatsBioNet: Network Analysis for MS-based Proteomics Experiments}, author = {Anthony Wu and Olga Vitek}, year = {2024}, note = {R package version 0.99.5, https://vitek-lab.github.io/MSstatsBioNet/}, url = {http://msstats.org}, }"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"msstatsbionet","dir":"","previous_headings":"","what":"Network Analysis for MS-based Proteomics Experiments","title":"Network Analysis for MS-based Proteomics Experiments","text":"package provides suite functions query various network databases, filter queries & results, visualize networks.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"installation-instructions","dir":"","previous_headings":"","what":"Installation Instructions","title":"Network Analysis for MS-based Proteomics Experiments","text":"install package bioconductor, run following command: can install development version package Github:","code":"if (!require(\"BiocManager\", quietly = TRUE)) install.packages(\"BiocManager\") BiocManager::install(\"MSstatsBioNet\") devtools::install_github(\"Vitek-Lab/MSstatsConvert\", build_vignettes = TRUE)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Network Analysis for MS-based Proteomics Experiments","text":"package distributed Artistic-2.0 license. However, dependencies may different licenses. Notably, INDRA distributed BSD 2-Clause license. Furthermore, INDRA’s knowledge sources may different licenses commercial applications. Please refer INDRA README information knowledge sources associated licenses.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"databases-supported","dir":"","previous_headings":"","what":"Databases Supported","title":"Network Analysis for MS-based Proteomics Experiments","text":"INDRA","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"filtering-options-supported","dir":"","previous_headings":"","what":"Filtering Options Supported","title":"Network Analysis for MS-based Proteomics Experiments","text":"P-Value Filter","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"visualization-options-supported","dir":"","previous_headings":"","what":"Visualization Options Supported","title":"Network Analysis for MS-based Proteomics Experiments","text":"Cytoscape Desktop","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/getSubnetworkFromIndra.html","id":null,"dir":"Reference","previous_headings":"","what":"Get subnetwork from INDRA database — getSubnetworkFromIndra","title":"Get subnetwork from INDRA database — getSubnetworkFromIndra","text":"Using differential abundance results MSstats, function retrieves subnetwork protein interactions INDRA database.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/getSubnetworkFromIndra.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get subnetwork from INDRA database — getSubnetworkFromIndra","text":"","code":"getSubnetworkFromIndra(input, pvalueCutoff = NULL)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/getSubnetworkFromIndra.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get subnetwork from INDRA database — getSubnetworkFromIndra","text":"input output groupComparison function's comparisionResult table, contains list proteins corresponding p-values, logFCs, along additional HGNC ID HGNC name columns pvalueCutoff p-value cutoff filtering. Default NULL, .e. filtering","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/getSubnetworkFromIndra.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get subnetwork from INDRA database — getSubnetworkFromIndra","text":"list 2 data.frames, nodes edges","code":""},{"path":[]},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/getSubnetworkFromIndra.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get subnetwork from INDRA database — getSubnetworkFromIndra","text":"","code":"input <- data.table::fread(system.file( \"extdata/groupComparisonModel.csv\", package = \"MSstatsBioNet\" )) subnetwork <- getSubnetworkFromIndra(input, pvalueCutoff = 0.05) #> Warning: NOTICE: This function includes third-party software components #> that are licensed under the BSD 2-Clause License. Please ensure to #> include the third-party licensing agreements if redistributing this #> package or utilizing the results based on this package. #> See the LICENSE file for more details. head(subnetwork$nodes) #> [1] id logFC pvalue #> <0 rows> (or 0-length row.names) head(subnetwork$edges) #> [1] source target interaction evidenceCount evidenceLink #> <0 rows> (or 0-length row.names)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":null,"dir":"Reference","previous_headings":"","what":"Create visualization of network — visualizeNetworks","title":"Create visualization of network — visualizeNetworks","text":"Use results INDRA generate visualization network Cytoscape Desktop. Note Cytoscape Desktop app must open function work.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create visualization of network — visualizeNetworks","text":"","code":"visualizeNetworks(nodes, edges, pvalueCutoff = 0.05, logfcCutoff = 0.5)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create visualization of network — visualizeNetworks","text":"nodes dataframe nodes consisting columns id (chararacter), pvalue (number), logFC (number) edges dataframe edges consisting columns source (character), target (character), interaction (character), evidenceCount (number), evidenceLink (character) pvalueCutoff p-value cutoff coloring significant proteins. Default 0.05 logfcCutoff log fold change cutoff coloring significant proteins. Default 0.5","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create visualization of network — visualizeNetworks","text":"cytoscape visualization subnetwork","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create visualization of network — visualizeNetworks","text":"","code":"input <- data.table::fread(system.file( \"extdata/groupComparisonModel.csv\", package = \"MSstatsBioNet\" )) subnetwork <- getSubnetworkFromIndra(input) #> Warning: NOTICE: This function includes third-party software components #> that are licensed under the BSD 2-Clause License. Please ensure to #> include the third-party licensing agreements if redistributing this #> package or utilizing the results based on this package. #> See the LICENSE file for more details. visualizeNetworks(subnetwork$nodes, subnetwork$edges) #> Warning: Visualization is not available in non-interactive mode."},{"path":"https://vitek-lab.github.io/MSstatsBioNet/news/index.html","id":"msstatsbionet-0990","dir":"Changelog","previous_headings":"","what":"MSstatsBioNet 0.99.0","title":"MSstatsBioNet 0.99.0","text":"Added function getSubnetworkFromIndra extract biomolecular subnetworks INDRA database. Added function visualizeNetworks visualize networks Cytoscape desktop. Added vignette","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/news/index.html","id":"msstatsbionet-010","dir":"Changelog","previous_headings":"","what":"MSstatsBioNet 0.1.0","title":"MSstatsBioNet 0.1.0","text":"Added NEWS.md file track changes package.","code":""}]
+[{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"installation","dir":"Articles","previous_headings":"","what":"Installation","title":"MSstatsBioNet Introduction","text":"Run code install MSstatsBioNet bioconductor","code":"if (!require(\"BiocManager\", quietly = TRUE)) { install.packages(\"BiocManager\") } BiocManager::install(\"MSstatsBioNet\")"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"purpose-of-msstatsbionet","dir":"Articles","previous_headings":"","what":"Purpose of MSstatsBioNet","title":"MSstatsBioNet Introduction","text":"MSstatsBioNet package member MSstats family packages. contains set functions interpretation mass spectrometry (MS) statistical analysis results context protein-protein interaction networks. package designed used conjunction MSstats package.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"msstats-convert-from-upstream-dataset","dir":"Articles","previous_headings":"","what":"MSstats Convert from Upstream Dataset","title":"MSstatsBioNet Introduction","text":"first convert input data format can processed MSstats. example, MetamorpheusToMSstatsFormat function used convert input data Metamorpheus MSstats format. MSstats format contain necessary information downstream analysis, peptide information, abundance values, run ID, experimental annotation information.","code":"library(MSstatsConvert) input <- system.file(\"tinytest/raw_data/Metamorpheus/AllQuantifiedPeaks.tsv\", package = \"MSstatsConvert\" ) input <- data.table::fread(input) annot <- system.file(\"tinytest/raw_data/Metamorpheus/Annotation.tsv\", package = \"MSstatsConvert\" ) annot <- data.table::fread(annot) msstats_imported <- MetamorpheusToMSstatsFormat(input, annotation = annot, use_log_file = FALSE ) #> INFO [2024-11-06 17:07:29] ** Raw data from Metamorpheus imported successfully. #> INFO [2024-11-06 17:07:29] ** Raw data from Metamorpheus cleaned successfully. #> INFO [2024-11-06 17:07:29] ** Using provided annotation. #> INFO [2024-11-06 17:07:29] ** Run labels were standardized to remove symbols such as '.' or '%'. #> INFO [2024-11-06 17:07:29] ** The following options are used: #> - Features will be defined by the columns: PeptideSequence, PrecursorCharge #> - Shared peptides will be removed. #> - Proteins with single feature will not be removed. #> - Features with less than 3 measurements across runs will be removed. #> INFO [2024-11-06 17:07:29] ** Features with all missing measurements across runs are removed. #> INFO [2024-11-06 17:07:29] ** Shared peptides are removed. #> INFO [2024-11-06 17:07:29] ** Multiple measurements in a feature and a run are summarized by summaryforMultipleRows: max #> INFO [2024-11-06 17:07:29] ** Features with one or two measurements across runs are removed. #> INFO [2024-11-06 17:07:29] ** Run annotation merged with quantification data. #> INFO [2024-11-06 17:07:29] ** Features with one or two measurements across runs are removed. #> INFO [2024-11-06 17:07:29] ** Fractionation handled. #> INFO [2024-11-06 17:07:29] ** Updated quantification data to make balanced design. Missing values are marked by NA #> INFO [2024-11-06 17:07:29] ** Finished preprocessing. The dataset is ready to be processed by the dataProcess function. head(msstats_imported) #> ProteinName PeptideSequence #> 1 O43707 AC[Common Fixed:Carbamidomethyl on C]LISLGYDVENDRQGEAEFNR #> 2 O43707 AC[Common Fixed:Carbamidomethyl on C]LISLGYDVENDRQGEAEFNR #> 3 O43707 AC[Common Fixed:Carbamidomethyl on C]LISLGYDVENDRQGEAEFNR #> 4 O43707 AC[Common Fixed:Carbamidomethyl on C]LISLGYDVENDRQGEAEFNR #> 5 B9A064 AGVETTKPSK #> 6 B9A064 AGVETTKPSK #> PrecursorCharge FragmentIon ProductCharge IsotopeLabelType Condition #> 1 3 NA NA L neg #> 2 3 NA NA L neg #> 3 3 NA NA L pos #> 4 3 NA NA L pos #> 5 2 NA NA L neg #> 6 2 NA NA L neg #> BioReplicate Run Fraction Intensity #> 1 1 NEG1-calib 1 NA #> 2 2 NEG2-calib 1 655481.2 #> 3 3 POS1-calib 1 496891.9 #> 4 4 POS2-calib 1 213691.0 #> 5 1 NEG1-calib 1 4201663.3 #> 6 2 NEG2-calib 1 4427577.4"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"msstats-process-and-groupcomparison","dir":"Articles","previous_headings":"","what":"MSstats Process and GroupComparison","title":"MSstatsBioNet Introduction","text":"Next, preprocess data using dataProcess function perform statistical analysis using groupComparison function. output groupComparison table containing list differentially abundant proteins associated p-values log fold changes.","code":"library(MSstats) #> #> Attaching package: 'MSstats' #> The following objects are masked from 'package:MSstatsConvert': #> #> DIANNtoMSstatsFormat, DIAUmpiretoMSstatsFormat, #> FragPipetoMSstatsFormat, MaxQtoMSstatsFormat, #> OpenMStoMSstatsFormat, OpenSWATHtoMSstatsFormat, PDtoMSstatsFormat, #> ProgenesistoMSstatsFormat, SkylinetoMSstatsFormat, #> SpectronauttoMSstatsFormat #> The following object is masked from 'package:grDevices': #> #> savePlot QuantData <- dataProcess(msstats_imported, use_log_file = FALSE) #> INFO [2024-11-06 17:07:30] ** Log2 intensities under cutoff = 16.018 were considered as censored missing values. #> INFO [2024-11-06 17:07:30] ** Log2 intensities = NA were considered as censored missing values. #> INFO [2024-11-06 17:07:30] ** Use all features that the dataset originally has. #> INFO [2024-11-06 17:07:30] #> # proteins: 7 #> # peptides per protein: 1-26 #> # features per peptide: 1-1 #> INFO [2024-11-06 17:07:30] Some proteins have only one feature: #> O00391 ... #> INFO [2024-11-06 17:07:30] #> neg pos #> # runs 2 2 #> # bioreplicates 2 2 #> # tech. replicates 1 1 #> INFO [2024-11-06 17:07:30] == Start the summarization per subplot... #> | | | 0% | |========== | 14% | |==================== | 29% | |============================== | 43% | |======================================== | 57% | |================================================== | 71% | |============================================================ | 86% | |======================================================================| 100% #> INFO [2024-11-06 17:07:30] == Summarization is done. groupComparisonResult <- groupComparison( contrast.matrix = \"pairwise\", data = QuantData, use_log_file = FALSE ) #> INFO [2024-11-06 17:07:30] == Start to test and get inference in whole plot ... #> | | | 0% | |========== | 14% | |==================== | 29% | |============================== | 43% | |======================================== | 57% | |================================================== | 71% | |============================================================ | 86% | |======================================================================| 100% #> INFO [2024-11-06 17:07:31] == Comparisons for all proteins are done."},{"path":[]},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"id-conversion","dir":"Articles","previous_headings":"MSstatsBioNet Analysis","what":"ID Conversion","title":"MSstatsBioNet Introduction","text":"First, need convert group comparison results format can processed INDRA. getSubnetworkFromIndra function requires table containing HGNC IDs. can use following mapping convert Uniprot HGNC ID. mapping obtained Python uniprot client future, uniprot client added separate function allow users perform conversion R streamlined way.","code":"library(MSstatsBioNet) uniprot_to_hgnc_mapping <- c( \"B9A064\" = \"38476\", \"O00391\" = \"9756\", \"O14818\" = \"9536\", \"O43598\" = \"21218\", \"O43707\" = \"166\", \"P16050\" = \"11390\", \"P84243\" = \"4765\" ) groupComparisonResult$ComparisonResult$HgncId <- uniprot_to_hgnc_mapping[ groupComparisonResult$ComparisonResult$Protein ]"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"subnetwork-query","dir":"Articles","previous_headings":"MSstatsBioNet Analysis","what":"Subnetwork Query","title":"MSstatsBioNet Introduction","text":"package provides function getSubnetworkFromIndra retrieves subnetwork proteins INDRA database based differential abundance analysis results. package distributed Artistic-2.0 license. However, dependencies may different licenses. example, getSubnetworkFromIndra depends INDRA, distributed BSD 2-Clause license. Furthermore, INDRA’s knowledge sources may different licenses commercial applications. Please refer INDRA README information knowledge sources associated licenses.","code":"subnetwork <- getSubnetworkFromIndra(groupComparisonResult$ComparisonResult) #> Warning in getSubnetworkFromIndra(groupComparisonResult$ComparisonResult): NOTICE: This function includes third-party software components #> that are licensed under the BSD 2-Clause License. Please ensure to #> include the third-party licensing agreements if redistributing this #> package or utilizing the results based on this package. #> See the LICENSE file for more details."},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"visualize-networks","dir":"Articles","previous_headings":"MSstatsBioNet Analysis","what":"Visualize Networks","title":"MSstatsBioNet Introduction","text":"function visualizeNetworks takes output getSubnetworkFromIndra visualizes subnetwork. function requires Cytoscape desktop open visualization work. network diagram displayed Cytoscape, see two arrows connecting two nodes, P16050 P84243. arrows represent interactions two proteins, notably activation phosphorylation.","code":"visualizeNetworks(subnetwork$nodes, subnetwork$edges) #> Warning in visualizeNetworks(subnetwork$nodes, subnetwork$edges): Visualization #> is not available in non-interactive mode."},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"session-info","dir":"Articles","previous_headings":"","what":"Session info","title":"MSstatsBioNet Introduction","text":"","code":"sessionInfo() #> R version 4.4.2 (2024-10-31) #> Platform: x86_64-pc-linux-gnu #> Running under: Ubuntu 22.04.5 LTS #> #> Matrix products: default #> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 #> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0 #> #> locale: #> [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8 #> [4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8 #> [7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C #> [10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C #> #> time zone: UTC #> tzcode source: system (glibc) #> #> attached base packages: #> [1] stats graphics grDevices utils datasets methods base #> #> other attached packages: #> [1] MSstatsBioNet_0.99.5 MSstats_4.14.0 MSstatsConvert_1.16.0 #> [4] BiocStyle_2.34.0 #> #> loaded via a namespace (and not attached): #> [1] tidyselect_1.2.1 viridisLite_0.4.2 IRdisplay_1.1 #> [4] dplyr_1.1.4 bitops_1.0-9 RCurl_1.98-1.16 #> [7] fastmap_1.2.0 lazyeval_0.2.2 base64url_1.4 #> [10] XML_3.99-0.17 digest_0.6.37 lifecycle_1.0.4 #> [13] survival_3.7-0 statmod_1.5.0 r2r_0.1.1 #> [16] magrittr_2.0.3 compiler_4.4.2 rlang_1.1.4 #> [19] sass_0.4.9 tools_4.4.2 utf8_1.2.4 #> [22] yaml_2.3.10 data.table_1.16.2 knitr_1.48 #> [25] htmlwidgets_1.6.4 curl_5.2.3 marray_1.84.0 #> [28] RColorBrewer_1.1-3 repr_1.1.7 KernSmooth_2.23-24 #> [31] pbdZMQ_0.3-13 purrr_1.0.2 BiocGenerics_0.52.0 #> [34] desc_1.4.3 stats4_4.4.2 grid_4.4.2 #> [37] preprocessCore_1.68.0 fansi_1.0.6 caTools_1.18.3 #> [40] colorspace_2.1-1 log4r_0.4.4 ggplot2_3.5.1 #> [43] scales_1.3.0 gtools_3.9.5 MASS_7.3-61 #> [46] cli_3.6.3 rmarkdown_2.29 crayon_1.5.3 #> [49] ragg_1.3.3 generics_0.1.3 httr_1.4.7 #> [52] minqa_1.2.8 cachem_1.1.0 splines_4.4.2 #> [55] parallel_4.4.2 BiocManager_1.30.25 base64enc_0.1-3 #> [58] vctrs_0.6.5 boot_1.3-31 Matrix_1.7-1 #> [61] jsonlite_1.8.9 bookdown_0.41 ggrepel_0.9.6 #> [64] systemfonts_1.1.0 limma_3.62.1 plotly_4.10.4 #> [67] jquerylib_0.1.4 tidyr_1.3.1 glue_1.8.0 #> [70] nloptr_2.1.1 pkgdown_2.1.1 RJSONIO_1.3-1.9 #> [73] stringi_1.8.4 gtable_0.3.6 lme4_1.1-35.5 #> [76] munsell_0.5.1 tibble_3.2.1 pillar_1.9.0 #> [79] htmltools_0.5.8.1 gplots_3.2.0 RCy3_2.26.0 #> [82] graph_1.84.0 IRkernel_1.3.2 R6_2.5.1 #> [85] textshaping_0.4.0 evaluate_1.0.1 lattice_0.22-6 #> [88] backports_1.5.0 bslib_0.8.0 Rcpp_1.0.13-1 #> [91] uuid_1.2-1 nlme_3.1-166 checkmate_2.3.2 #> [94] xfun_0.49 fs_1.6.5 pkgconfig_2.0.3"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Anthony Wu. Author, maintainer. Olga Vitek. Author.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Wu , Vitek O (2024). MSstatsBioNet: Network Analysis MS-based Proteomics Experiments. R package version 0.99.5, https://vitek-lab.github.io/MSstatsBioNet/, http://msstats.org.","code":"@Manual{, title = {MSstatsBioNet: Network Analysis for MS-based Proteomics Experiments}, author = {Anthony Wu and Olga Vitek}, year = {2024}, note = {R package version 0.99.5, https://vitek-lab.github.io/MSstatsBioNet/}, url = {http://msstats.org}, }"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"msstatsbionet","dir":"","previous_headings":"","what":"Network Analysis for MS-based Proteomics Experiments","title":"Network Analysis for MS-based Proteomics Experiments","text":"package provides suite functions query various network databases, filter queries & results, visualize networks.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"installation-instructions","dir":"","previous_headings":"","what":"Installation Instructions","title":"Network Analysis for MS-based Proteomics Experiments","text":"install package bioconductor, run following command: can install development version package Github:","code":"if (!require(\"BiocManager\", quietly = TRUE)) install.packages(\"BiocManager\") BiocManager::install(\"MSstatsBioNet\") devtools::install_github(\"Vitek-Lab/MSstatsConvert\", build_vignettes = TRUE)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Network Analysis for MS-based Proteomics Experiments","text":"package distributed Artistic-2.0 license. However, dependencies may different licenses. Notably, INDRA distributed BSD 2-Clause license. Furthermore, INDRA’s knowledge sources may different licenses commercial applications. Please refer INDRA README information knowledge sources associated licenses.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"databases-supported","dir":"","previous_headings":"","what":"Databases Supported","title":"Network Analysis for MS-based Proteomics Experiments","text":"INDRA","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"filtering-options-supported","dir":"","previous_headings":"","what":"Filtering Options Supported","title":"Network Analysis for MS-based Proteomics Experiments","text":"P-Value Filter","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/index.html","id":"visualization-options-supported","dir":"","previous_headings":"","what":"Visualization Options Supported","title":"Network Analysis for MS-based Proteomics Experiments","text":"Cytoscape Desktop","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/getSubnetworkFromIndra.html","id":null,"dir":"Reference","previous_headings":"","what":"Get subnetwork from INDRA database — getSubnetworkFromIndra","title":"Get subnetwork from INDRA database — getSubnetworkFromIndra","text":"Using differential abundance results MSstats, function retrieves subnetwork protein interactions INDRA database.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/getSubnetworkFromIndra.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get subnetwork from INDRA database — getSubnetworkFromIndra","text":"","code":"getSubnetworkFromIndra(input, pvalueCutoff = NULL)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/getSubnetworkFromIndra.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get subnetwork from INDRA database — getSubnetworkFromIndra","text":"input output groupComparison function's comparisionResult table, contains list proteins corresponding p-values, logFCs, along additional HGNC ID HGNC name columns pvalueCutoff p-value cutoff filtering. Default NULL, .e. filtering","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/getSubnetworkFromIndra.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get subnetwork from INDRA database — getSubnetworkFromIndra","text":"list 2 data.frames, nodes edges","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/getSubnetworkFromIndra.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get subnetwork from INDRA database — getSubnetworkFromIndra","text":"","code":"input <- data.table::fread(system.file( \"extdata/groupComparisonModel.csv\", package = \"MSstatsBioNet\" )) subnetwork <- getSubnetworkFromIndra(input, pvalueCutoff = 0.05) #> Warning: NOTICE: This function includes third-party software components #> that are licensed under the BSD 2-Clause License. Please ensure to #> include the third-party licensing agreements if redistributing this #> package or utilizing the results based on this package. #> See the LICENSE file for more details. head(subnetwork$nodes) #> [1] id logFC pvalue #> <0 rows> (or 0-length row.names) head(subnetwork$edges) #> [1] source target interaction evidenceCount evidenceLink #> <0 rows> (or 0-length row.names)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":null,"dir":"Reference","previous_headings":"","what":"Create visualization of network — visualizeNetworks","title":"Create visualization of network — visualizeNetworks","text":"Use results INDRA generate visualization network Cytoscape Desktop. Note Cytoscape Desktop app must open function work.","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create visualization of network — visualizeNetworks","text":"","code":"visualizeNetworks(nodes, edges, pvalueCutoff = 0.05, logfcCutoff = 0.5)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create visualization of network — visualizeNetworks","text":"nodes dataframe nodes consisting columns id (chararacter), pvalue (number), logFC (number) edges dataframe edges consisting columns source (character), target (character), interaction (character), evidenceCount (number), evidenceLink (character) pvalueCutoff p-value cutoff coloring significant proteins. Default 0.05 logfcCutoff log fold change cutoff coloring significant proteins. Default 0.5","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create visualization of network — visualizeNetworks","text":"cytoscape visualization subnetwork","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create visualization of network — visualizeNetworks","text":"","code":"input <- data.table::fread(system.file( \"extdata/groupComparisonModel.csv\", package = \"MSstatsBioNet\" )) subnetwork <- getSubnetworkFromIndra(input) #> Warning: NOTICE: This function includes third-party software components #> that are licensed under the BSD 2-Clause License. Please ensure to #> include the third-party licensing agreements if redistributing this #> package or utilizing the results based on this package. #> See the LICENSE file for more details. visualizeNetworks(subnetwork$nodes, subnetwork$edges) #> Warning: Visualization is not available in non-interactive mode."},{"path":"https://vitek-lab.github.io/MSstatsBioNet/news/index.html","id":"msstatsbionet-0990","dir":"Changelog","previous_headings":"","what":"MSstatsBioNet 0.99.0","title":"MSstatsBioNet 0.99.0","text":"Added function getSubnetworkFromIndra extract biomolecular subnetworks INDRA database. Added function visualizeNetworks visualize networks Cytoscape desktop. Added vignette","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/news/index.html","id":"msstatsbionet-010","dir":"Changelog","previous_headings":"","what":"MSstatsBioNet 0.1.0","title":"MSstatsBioNet 0.1.0","text":"Added NEWS.md file track changes package.","code":""}]