Chapter 7 Additional materials and session information

7.1 Additional materials

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• The Single-cell proteomics data analysis using QFeatures and scp workshop is provided as two vignettes. The first one provides a general introduction to the QFeatures class in the general context of mass spectrometry-based proteomics data manipulation. The second vignette focuses on single-cell application and introduces the scp package (⊕Vanderaa and Gatto 2021Vanderaa, Christophe, and Laurent Gatto. 2021. “Replication of Single-Cell Proteomics Data Reveals Important Computational Challenges.” Expert Rev. Proteomics, October.) as an extension of QFeatures. This second vignette also provides exercises that give the attendee the opportunity to apply the learned concepts to reproduce a published analysis on a subset of a real data set. A recent workshop, offered at the 2024 EuBIC winter school, provides teaching material for the new scplainer analysis workflow.

• A tutorial presenting Use Cases and Examples for Annotation of Untargeted Metabolomics Data using the MetaboAnnotation and MetaboCoreUtils packages (⊕Rainer et al. 2022Rainer, Johannes, Andrea Vicini, Liesa Salzer, Jan Stanstrup, Josep M Badia, Steffen Neumann, Michael A Stravs, et al. 2022. “A Modular and Expandable Ecosystem for Metabolomics Data Annotation in R.” Metabolites 12 (2): 173.).

• Exploring and analyzing LC-MS data with Spectra and xcms provides an overview of recent developments in Bioconductor to work with mass spectrometry (MsExperiment, Spectra) and specifically LC-MS data (xcms) and walks through the preprocessing of a small data set emphasizing on selection of data-dependent settings for the individual pre-processing steps.

The SpectraTutorials package provides three different vignettes:

• Seamless Integration of Mass Spectrometry Data from Different Sources: describes import/export of MS data from/to files in different format as well as processing and handling of MS data with the Spectra package.
• Spectra: an Expandable Infrastructure to Handle Mass Spectrometry Data: explains the concept of backends in Spectra, their properties, use cases along with performance considerations.
• MS/MS Spectra Matching with the MetaboAnnotation Package: explains how the Spectra package can be used together with the MetaboAnnotation package in LC-MS/MS annotation workflows for untargeted metabolomics data.

7.2 Compiling the book locally

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To compile and render the teaching material, you will also need the BiocStyle package and the (slighly modified) Modern Statistics for Model Biology (msmb) HTML Book Style by Mike Smith:

BiocManager::install(c("bookdown", "BiocStyle", "lgatto/msmbstyle"))

Clone the book repository and render the book with

bookdown::render_book(".")

7.3 Session information

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The following packages have been used to generate this document.

sessionInfo()

## R version 4.4.1 (2024-06-14)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.2 LTS
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## time zone: Europe/Brussels
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## attached base packages:
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## other attached packages:
##  [1] mzID_1.44.0                 patchwork_1.3.0            
##  [3] factoextra_1.0.7            gplots_3.2.0               
##  [5] limma_3.62.2                lubridate_1.9.4            
##  [7] forcats_1.0.0               stringr_1.5.1              
##  [9] purrr_1.0.4                 readr_2.1.5                
## [11] tibble_3.2.1                tidyverse_2.0.0            
## [13] MSnID_1.40.0                magrittr_2.0.3             
## [15] tidyr_1.3.1                 ggplot2_3.5.1              
## [17] dplyr_1.1.4                 msdata_0.46.0              
## [19] MsDataHub_1.7.1             rpx_2.14.1                 
## [21] MsCoreUtils_1.18.0          QFeatures_1.17.3           
## [23] MultiAssayExperiment_1.32.0 SummarizedExperiment_1.36.0
## [25] Biobase_2.66.0              GenomicRanges_1.58.0       
## [27] GenomeInfoDb_1.42.3         IRanges_2.40.1             
## [29] MatrixGenerics_1.18.1       matrixStats_1.5.0          
## [31] Spectra_1.16.0              BiocParallel_1.40.0        
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##  [64] pkgconfig_2.0.3         gtable_0.3.6            blob_1.2.4             
##  [67] impute_1.80.0           XVector_0.46.0          htmltools_0.5.8.1      
##  [70] carData_3.0-5           bookdown_0.34.2         MALDIquant_1.22.3      
##  [73] ProtGenerics_1.38.0     clue_0.3-66             scales_1.3.0           
##  [76] png_0.1-8               knitr_1.49              MetaboCoreUtils_1.14.0 
##  [79] rstudioapi_0.17.1       tzdb_0.4.0              reshape2_1.4.4         
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##  [85] BiocVersion_3.20.0      KernSmooth_2.23-24      parallel_4.4.1         
##  [88] AnnotationDbi_1.68.0    vsn_3.74.0              msmbstyle_0.0.22       
##  [91] pillar_1.10.1           grid_4.4.1              vctrs_0.6.5            
##  [94] pcaMethods_1.98.0       ggpubr_0.6.0            car_3.1-3              
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