From 2c0e759d770e7016ba3b4e34f18af59781cd2a8a Mon Sep 17 00:00:00 2001 From: tonywu1999 Date: Tue, 27 Aug 2024 19:57:26 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20Vitek-La?= =?UTF-8?q?b/MSstatsBioNet@d1735272a205ad95e62a91b2a09d2857975f09fb=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- articles/MSstatsBioNet.html | 201 ++++++++++++++++++++++---- pkgdown.yml | 2 +- reference/getSubnetworkFromIndra.html | 2 +- reference/visualizeNetworks.html | 2 +- search.json | 2 +- 5 files changed, 176 insertions(+), 33 deletions(-) diff --git a/articles/MSstatsBioNet.html b/articles/MSstatsBioNet.html index d9f756e..2fd0b0b 100644 --- a/articles/MSstatsBioNet.html +++ b/articles/MSstatsBioNet.html @@ -70,19 +70,143 @@

Purpose of MSstatsBioNetMSstats package.

+ +
+

MSstats Convert from Upstream Dataset +

+
+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  [2024-08-27 19:57:19] ** Raw data from Metamorpheus imported successfully.
+#> INFO  [2024-08-27 19:57:19] ** Raw data from Metamorpheus cleaned successfully.
+#> INFO  [2024-08-27 19:57:19] ** Using provided annotation.
+#> INFO  [2024-08-27 19:57:19] ** Run labels were standardized to remove symbols such as '.' or '%'.
+#> INFO  [2024-08-27 19:57:19] ** 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  [2024-08-27 19:57:19] ** Features with all missing measurements across runs are removed.
+#> INFO  [2024-08-27 19:57:19] ** Shared peptides are removed.
+#> INFO  [2024-08-27 19:57:19] ** Multiple measurements in a feature and a run are summarized by summaryforMultipleRows: max
+#> INFO  [2024-08-27 19:57:19] ** Features with one or two measurements across runs are removed.
+#> INFO  [2024-08-27 19:57:19] ** Run annotation merged with quantification data.
+#> INFO  [2024-08-27 19:57:19] ** Features with one or two measurements across runs are removed.
+#> INFO  [2024-08-27 19:57:19] ** Fractionation handled.
+#> INFO  [2024-08-27 19:57:19] ** Updated quantification data to make balanced design. Missing values are marked by NA
+#> INFO  [2024-08-27 19:57:19] ** 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
+
+
+

MSstats Process and GroupComparison +

+
+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  [2024-08-27 19:57:20] ** Log2 intensities under cutoff = 16.018  were considered as censored missing values.
+#> INFO  [2024-08-27 19:57:20] ** Log2 intensities = NA were considered as censored missing values.
+#> INFO  [2024-08-27 19:57:20] ** Use all features that the dataset originally has.
+#> INFO  [2024-08-27 19:57:20] 
+#>  # proteins: 7
+#>  # peptides per protein: 1-26
+#>  # features per peptide: 1-1
+#> INFO  [2024-08-27 19:57:20] Some proteins have only one feature: 
+#>  O00391 ...
+#> INFO  [2024-08-27 19:57:20] 
+#>                     neg pos
+#>              # runs   2   2
+#>     # bioreplicates   2   2
+#>  # tech. replicates   1   1
+#> INFO  [2024-08-27 19:57:20]  == Start the summarization per subplot...
+#>   |                                                                              |                                                                      |   0%  |                                                                              |==========                                                            |  14%  |                                                                              |====================                                                  |  29%  |                                                                              |==============================                                        |  43%  |                                                                              |========================================                              |  57%  |                                                                              |==================================================                    |  71%  |                                                                              |============================================================          |  86%  |                                                                              |======================================================================| 100%
+#> INFO  [2024-08-27 19:57:20]  == Summarization is done.
+groupComparisonResult = groupComparison(contrast.matrix="pairwise", 
+                                        data=QuantData, 
+                                        use_log_file = FALSE)
+#> INFO  [2024-08-27 19:57:20]  == Start to test and get inference in whole plot ...
+#>   |                                                                              |                                                                      |   0%  |                                                                              |==========                                                            |  14%  |                                                                              |====================                                                  |  29%  |                                                                              |==============================                                        |  43%  |                                                                              |========================================                              |  57%  |                                                                              |==================================================                    |  71%  |                                                                              |============================================================          |  86%  |                                                                              |======================================================================| 100%
+#> INFO  [2024-08-27 19:57:20]  == Comparisons for all proteins are done.
+
+
+

MSstatsBioNet Analysis +

+
+

ID Conversion +

+

First, we need to convert the group comparison results to a format +that can be processed by INDRA. The getSubnetworkFromIndra +function requires a table containing HGNC IDs. We can use the following +mapping to convert from Uniprot to HGNC ID. This mapping was obtained +from this Python +uniprot client

+

In the future, this uniprot client will be added as a separate +function to allow users to perform this conversion in R in a streamlined +way.

+
+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
+]
+
+
+

Subnetwork Query +

The package provides a function getSubnetworkFromIndra that retrieves a subnetwork of proteins from the INDRA database based on differential abundance analysis results. The function visualizeNetworks then takes the output of getSubnetworkFromIndra and visualizes the subnetwork.

-
-input <- data.table::fread(
-    system.file("processed_data/groupComparisonModel.csv",
-        package = "MSstatsBioNet"
-    )
-)
-subnetwork <- getSubnetworkFromIndra(input)
-visualizeNetworks(subnetwork$nodes, subnetwork$edges)
+
+
+subnetwork = getSubnetworkFromIndra(groupComparisonResult$ComparisonResult)

This package is distributed under the Artistic-2.0 license. However, its dependencies may have different licenses. In this example, getSubnetworkFromIndra depends on INDRA, which is distributed @@ -92,10 +216,17 @@

Purpose of MSstatsBioNet for more information on its knowledge sources and their associated licenses.

+
+

Visualize Networks +

+
+visualizeNetworks(subnetwork$nodes, subnetwork$edges)
+
+

Session info

-
+
+#>  [1] tidyselect_1.2.1      viridisLite_0.4.2     IRdisplay_1.1        
+#>  [4] dplyr_1.1.4           bitops_1.0-8          lazyeval_0.2.2       
+#>  [7] fastmap_1.2.0         RCurl_1.98-1.16       XML_3.99-0.17        
+#> [10] digest_0.6.37         base64url_1.4         lifecycle_1.0.4      
+#> [13] survival_3.6-4        statmod_1.5.0         magrittr_2.0.3       
+#> [16] compiler_4.4.1        r2r_0.1.1             rlang_1.1.4          
+#> [19] sass_0.4.9            tools_4.4.1           utf8_1.2.4           
+#> [22] yaml_2.3.10           data.table_1.15.4     knitr_1.48           
+#> [25] htmlwidgets_1.6.4     marray_1.82.0         repr_1.1.7           
+#> [28] RColorBrewer_1.1-3    KernSmooth_2.23-24    pbdZMQ_0.3-11        
+#> [31] purrr_1.0.2           BiocGenerics_0.50.0   desc_1.4.3           
+#> [34] grid_4.4.1            stats4_4.4.1          preprocessCore_1.66.0
+#> [37] fansi_1.0.6           caTools_1.18.2        colorspace_2.1-1     
+#> [40] log4r_0.4.3           ggplot2_3.5.1         scales_1.3.0         
+#> [43] gtools_3.9.5          MASS_7.3-60.2         cli_3.6.3            
+#> [46] rmarkdown_2.28        crayon_1.5.3          ragg_1.3.2           
+#> [49] generics_0.1.3        httr_1.4.7            minqa_1.2.8          
+#> [52] cachem_1.1.0          splines_4.4.1         parallel_4.4.1       
+#> [55] base64enc_0.1-3       vctrs_0.6.5           boot_1.3-30          
+#> [58] Matrix_1.7-0          jsonlite_1.8.8        ggrepel_0.9.5        
+#> [61] systemfonts_1.1.0     plotly_4.10.4         limma_3.60.4         
+#> [64] tidyr_1.3.1           jquerylib_0.1.4       glue_1.7.0           
+#> [67] pkgdown_2.1.0         nloptr_2.1.1          RJSONIO_1.3-1.9      
+#> [70] stringi_1.8.4         gtable_0.3.5          lme4_1.1-35.5        
+#> [73] munsell_0.5.1         tibble_3.2.1          pillar_1.9.0         
+#> [76] htmltools_0.5.8.1     gplots_3.1.3.1        RCy3_2.24.0          
+#> [79] IRkernel_1.3.2        graph_1.82.0          R6_2.5.1             
+#> [82] textshaping_0.4.0     evaluate_0.24.0       lattice_0.22-6       
+#> [85] backports_1.5.0       bslib_0.8.0           Rcpp_1.0.13          
+#> [88] uuid_1.2-1            nlme_3.1-164          checkmate_2.3.2      
+#> [91] xfun_0.47             fs_1.6.4              pkgconfig_2.0.3
diff --git a/pkgdown.yml b/pkgdown.yml index fa860cc..8318e0f 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -3,7 +3,7 @@ pkgdown: 2.1.0 pkgdown_sha: ~ articles: MSstatsBioNet: MSstatsBioNet.html -last_built: 2024-08-27T18:14Z +last_built: 2024-08-27T19:57Z urls: reference: https://vitek-lab.github.io/MSstatsBioNet/reference article: https://vitek-lab.github.io/MSstatsBioNet/articles diff --git a/reference/getSubnetworkFromIndra.html b/reference/getSubnetworkFromIndra.html index 21ef5b9..13b67d4 100644 --- a/reference/getSubnetworkFromIndra.html +++ b/reference/getSubnetworkFromIndra.html @@ -64,7 +64,7 @@

Value

Examples

input <- data.table::fread(system.file(
-    "processed_data/groupComparisonModel.csv",
+    "extdata/groupComparisonModel.csv",
     package = "MSstatsBioNet"
 ))
 # subnetwork = getSubnetworkFromIndra(input, pvalue_cutoff = 0.05)
diff --git a/reference/visualizeNetworks.html b/reference/visualizeNetworks.html
index 0a901fe..bb79304 100644
--- a/reference/visualizeNetworks.html
+++ b/reference/visualizeNetworks.html
@@ -72,7 +72,7 @@ 
Value

     
Examples

     
input <- data.table::fread(system.file(
-    "processed_data/groupComparisonModel.csv",
+    "extdata/groupComparisonModel.csv",
     package = "MSstatsBioNet"
 ))
 # subnetwork = getSubnetworkFromIndra(input)
diff --git a/search.json b/search.json
index a27996c..7699e3a 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
-[{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"purpose-of-msstatsbionet","dir":"Articles","previous_headings":"","what":"Purpose of MSstatsBioNet","title":"MSstatsBioNet","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. package provides function getSubnetworkFromIndra retrieves subnetwork proteins INDRA database based differential abundance analysis results. function visualizeNetworks takes output getSubnetworkFromIndra visualizes subnetwork. 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":"input <- data.table::fread(     system.file(\"processed_data/groupComparisonModel.csv\",         package = \"MSstatsBioNet\"     ) ) subnetwork <- getSubnetworkFromIndra(input) visualizeNetworks(subnetwork$nodes, subnetwork$edges)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"session-info","dir":"Articles","previous_headings":"","what":"Session info","title":"MSstatsBioNet","text":"","code":"sessionInfo() #> R version 4.4.1 (2024-06-14) #> Platform: x86_64-pc-linux-gnu #> Running under: Ubuntu 22.04.4 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_0.99.1 #>  #> loaded via a namespace (and not attached): #>  [1] base64url_1.4       jsonlite_1.8.8      compiler_4.4.1      #>  [4] crayon_1.5.3        gtools_3.9.5        IRdisplay_1.1       #>  [7] bitops_1.0-8        RCy3_2.24.0         jquerylib_0.1.4     #> [10] systemfonts_1.1.0   textshaping_0.4.0   uuid_1.2-1          #> [13] yaml_2.3.10         fastmap_1.2.0       IRkernel_1.3.2      #> [16] R6_2.5.1            knitr_1.48          backports_1.5.0     #> [19] BiocGenerics_0.50.0 graph_1.82.0        XML_3.99-0.17       #> [22] desc_1.4.3          bslib_0.8.0         pillar_1.9.0        #> [25] RColorBrewer_1.1-3  rlang_1.1.4         utf8_1.2.4          #> [28] cachem_1.1.0        stringi_1.8.4       repr_1.1.7          #> [31] xfun_0.47           caTools_1.18.2      fs_1.6.4            #> [34] sass_0.4.9          RJSONIO_1.3-1.9     cli_3.6.3           #> [37] pkgdown_2.1.0       digest_0.6.37       base64enc_0.1-3     #> [40] pbdZMQ_0.3-11       lifecycle_1.0.4     r2r_0.1.1           #> [43] vctrs_0.6.5         KernSmooth_2.23-24  evaluate_0.24.0     #> [46] glue_1.7.0          ragg_1.3.2          stats4_4.4.1        #> [49] RCurl_1.98-1.16     fansi_1.0.6         rmarkdown_2.28      #> [52] httr_1.4.7          gplots_3.1.3.1      tools_4.4.1         #> [55] htmltools_0.5.8.1"},{"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 0.99.1, 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 0.99.1, 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 with differential analysis results — getSubnetworkFromIndra","title":"Get subnetwork from INDRA database with differential analysis results — getSubnetworkFromIndra","text":"Get subnetwork INDRA database differential analysis results","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 with differential analysis results — getSubnetworkFromIndra","text":"","code":"getSubnetworkFromIndra(input, pvalue_cutoff = 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 with differential analysis results — getSubnetworkFromIndra","text":"input groupComparison comparisionResult table additional HGNC ID HGNC name columns pvalue_cutoff 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 with differential analysis results — 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 with differential analysis results — getSubnetworkFromIndra","text":"","code":"input <- data.table::fread(system.file(     \"processed_data/groupComparisonModel.csv\",     package = \"MSstatsBioNet\" )) # subnetwork = getSubnetworkFromIndra(input, pvalue_cutoff = 0.05) # head(subnetwork$nodes) # head(subnetwork$edges)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":null,"dir":"Reference","previous_headings":"","what":"Create visualization of subnetwork in cytoscape — visualizeNetworks","title":"Create visualization of subnetwork in cytoscape — visualizeNetworks","text":"Create visualization subnetwork cytoscape","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create visualization of subnetwork in cytoscape — visualizeNetworks","text":"","code":"visualizeNetworks(nodes, edges, pvalue_cutoff = 0.05, logfc_cutoff = 0.5)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create visualization of subnetwork in cytoscape — visualizeNetworks","text":"nodes dataframe nodes edges dataframe edges pvalue_cutoff p-value cutoff coloring significant proteins. Default 0.05 logfc_cutoff 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 subnetwork in cytoscape — 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 subnetwork in cytoscape — visualizeNetworks","text":"","code":"input <- data.table::fread(system.file(     \"processed_data/groupComparisonModel.csv\",     package = \"MSstatsBioNet\" )) # subnetwork = getSubnetworkFromIndra(input) # visualizeNetworks(subnetwork$nodes, subnetwork$edges)"},{"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":"purpose-of-msstatsbionet","dir":"Articles","previous_headings":"","what":"Purpose of MSstatsBioNet","title":"MSstatsBioNet","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","text":"","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  [2024-08-27 19:57:19] ** Raw data from Metamorpheus imported successfully. #> INFO  [2024-08-27 19:57:19] ** Raw data from Metamorpheus cleaned successfully. #> INFO  [2024-08-27 19:57:19] ** Using provided annotation. #> INFO  [2024-08-27 19:57:19] ** Run labels were standardized to remove symbols such as '.' or '%'. #> INFO  [2024-08-27 19:57:19] ** 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  [2024-08-27 19:57:19] ** Features with all missing measurements across runs are removed. #> INFO  [2024-08-27 19:57:19] ** Shared peptides are removed. #> INFO  [2024-08-27 19:57:19] ** Multiple measurements in a feature and a run are summarized by summaryforMultipleRows: max #> INFO  [2024-08-27 19:57:19] ** Features with one or two measurements across runs are removed. #> INFO  [2024-08-27 19:57:19] ** Run annotation merged with quantification data. #> INFO  [2024-08-27 19:57:19] ** Features with one or two measurements across runs are removed. #> INFO  [2024-08-27 19:57:19] ** Fractionation handled. #> INFO  [2024-08-27 19:57:19] ** Updated quantification data to make balanced design. Missing values are marked by NA #> INFO  [2024-08-27 19:57:19] ** 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","text":"","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  [2024-08-27 19:57:20] ** Log2 intensities under cutoff = 16.018  were considered as censored missing values. #> INFO  [2024-08-27 19:57:20] ** Log2 intensities = NA were considered as censored missing values. #> INFO  [2024-08-27 19:57:20] ** Use all features that the dataset originally has. #> INFO  [2024-08-27 19:57:20]  #>  # proteins: 7 #>  # peptides per protein: 1-26 #>  # features per peptide: 1-1 #> INFO  [2024-08-27 19:57:20] Some proteins have only one feature:  #>  O00391 ... #> INFO  [2024-08-27 19:57:20]  #>                     neg pos #>              # runs   2   2 #>     # bioreplicates   2   2 #>  # tech. replicates   1   1 #> INFO  [2024-08-27 19:57:20]  == Start the summarization per subplot... #>   |                                                                              |                                                                      |   0%  |                                                                              |==========                                                            |  14%  |                                                                              |====================                                                  |  29%  |                                                                              |==============================                                        |  43%  |                                                                              |========================================                              |  57%  |                                                                              |==================================================                    |  71%  |                                                                              |============================================================          |  86%  |                                                                              |======================================================================| 100% #> INFO  [2024-08-27 19:57:20]  == Summarization is done. groupComparisonResult = groupComparison(contrast.matrix=\"pairwise\",                                          data=QuantData,                                          use_log_file = FALSE) #> INFO  [2024-08-27 19:57:20]  == Start to test and get inference in whole plot ... #>   |                                                                              |                                                                      |   0%  |                                                                              |==========                                                            |  14%  |                                                                              |====================                                                  |  29%  |                                                                              |==============================                                        |  43%  |                                                                              |========================================                              |  57%  |                                                                              |==================================================                    |  71%  |                                                                              |============================================================          |  86%  |                                                                              |======================================================================| 100% #> INFO  [2024-08-27 19:57:20]  == 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","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":"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","text":"package provides function getSubnetworkFromIndra retrieves subnetwork proteins INDRA database based differential abundance analysis results. function visualizeNetworks takes output getSubnetworkFromIndra visualizes subnetwork. 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$ComparisonResult)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"visualize-networks","dir":"Articles","previous_headings":"MSstatsBioNet Analysis","what":"Visualize Networks","title":"MSstatsBioNet","text":"","code":"visualizeNetworks(subnetwork$nodes, subnetwork$edges)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/articles/MSstatsBioNet.html","id":"session-info","dir":"Articles","previous_headings":"","what":"Session info","title":"MSstatsBioNet","text":"","code":"sessionInfo() #> R version 4.4.1 (2024-06-14) #> Platform: x86_64-pc-linux-gnu #> Running under: Ubuntu 22.04.4 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] MSstats_4.12.1        MSstatsConvert_1.14.0 MSstatsBioNet_0.99.1  #>  #> 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_1.0-8          lazyeval_0.2.2        #>  [7] fastmap_1.2.0         RCurl_1.98-1.16       XML_3.99-0.17         #> [10] digest_0.6.37         base64url_1.4         lifecycle_1.0.4       #> [13] survival_3.6-4        statmod_1.5.0         magrittr_2.0.3        #> [16] compiler_4.4.1        r2r_0.1.1             rlang_1.1.4           #> [19] sass_0.4.9            tools_4.4.1           utf8_1.2.4            #> [22] yaml_2.3.10           data.table_1.15.4     knitr_1.48            #> [25] htmlwidgets_1.6.4     marray_1.82.0         repr_1.1.7            #> [28] RColorBrewer_1.1-3    KernSmooth_2.23-24    pbdZMQ_0.3-11         #> [31] purrr_1.0.2           BiocGenerics_0.50.0   desc_1.4.3            #> [34] grid_4.4.1            stats4_4.4.1          preprocessCore_1.66.0 #> [37] fansi_1.0.6           caTools_1.18.2        colorspace_2.1-1      #> [40] log4r_0.4.3           ggplot2_3.5.1         scales_1.3.0          #> [43] gtools_3.9.5          MASS_7.3-60.2         cli_3.6.3             #> [46] rmarkdown_2.28        crayon_1.5.3          ragg_1.3.2            #> [49] generics_0.1.3        httr_1.4.7            minqa_1.2.8           #> [52] cachem_1.1.0          splines_4.4.1         parallel_4.4.1        #> [55] base64enc_0.1-3       vctrs_0.6.5           boot_1.3-30           #> [58] Matrix_1.7-0          jsonlite_1.8.8        ggrepel_0.9.5         #> [61] systemfonts_1.1.0     plotly_4.10.4         limma_3.60.4          #> [64] tidyr_1.3.1           jquerylib_0.1.4       glue_1.7.0            #> [67] pkgdown_2.1.0         nloptr_2.1.1          RJSONIO_1.3-1.9       #> [70] stringi_1.8.4         gtable_0.3.5          lme4_1.1-35.5         #> [73] munsell_0.5.1         tibble_3.2.1          pillar_1.9.0          #> [76] htmltools_0.5.8.1     gplots_3.1.3.1        RCy3_2.24.0           #> [79] IRkernel_1.3.2        graph_1.82.0          R6_2.5.1              #> [82] textshaping_0.4.0     evaluate_0.24.0       lattice_0.22-6        #> [85] backports_1.5.0       bslib_0.8.0           Rcpp_1.0.13           #> [88] uuid_1.2-1            nlme_3.1-164          checkmate_2.3.2       #> [91] xfun_0.47             fs_1.6.4              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 0.99.1, 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 0.99.1, 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 with differential analysis results — getSubnetworkFromIndra","title":"Get subnetwork from INDRA database with differential analysis results — getSubnetworkFromIndra","text":"Get subnetwork INDRA database differential analysis results","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 with differential analysis results — getSubnetworkFromIndra","text":"","code":"getSubnetworkFromIndra(input, pvalue_cutoff = 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 with differential analysis results — getSubnetworkFromIndra","text":"input groupComparison comparisionResult table additional HGNC ID HGNC name columns pvalue_cutoff 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 with differential analysis results — 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 with differential analysis results — getSubnetworkFromIndra","text":"","code":"input <- data.table::fread(system.file(     \"extdata/groupComparisonModel.csv\",     package = \"MSstatsBioNet\" )) # subnetwork = getSubnetworkFromIndra(input, pvalue_cutoff = 0.05) # head(subnetwork$nodes) # head(subnetwork$edges)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":null,"dir":"Reference","previous_headings":"","what":"Create visualization of subnetwork in cytoscape — visualizeNetworks","title":"Create visualization of subnetwork in cytoscape — visualizeNetworks","text":"Create visualization subnetwork cytoscape","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create visualization of subnetwork in cytoscape — visualizeNetworks","text":"","code":"visualizeNetworks(nodes, edges, pvalue_cutoff = 0.05, logfc_cutoff = 0.5)"},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create visualization of subnetwork in cytoscape — visualizeNetworks","text":"nodes dataframe nodes edges dataframe edges pvalue_cutoff p-value cutoff coloring significant proteins. Default 0.05 logfc_cutoff log fold change cutoff coloring significant proteins. Default 0.5","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create visualization of subnetwork in cytoscape — visualizeNetworks","text":"cytoscape visualization subnetwork","code":""},{"path":"https://vitek-lab.github.io/MSstatsBioNet/reference/visualizeNetworks.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create visualization of subnetwork in cytoscape — visualizeNetworks","text":"","code":"input <- data.table::fread(system.file(     \"extdata/groupComparisonModel.csv\",     package = \"MSstatsBioNet\" )) # subnetwork = getSubnetworkFromIndra(input) # visualizeNetworks(subnetwork$nodes, subnetwork$edges)"},{"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":""}]