1 Basics

1.1 Install chevreulPlot

R is an open-source statistical environment which can be easily modified to enhance its functionality via packages. chevreulPlot is a R package available via the Bioconductor repository for packages. R can be installed on any operating system from CRAN after which you can install chevreulPlot by using the following commands in your R session:

if (!requireNamespace("BiocManager", quietly = TRUE)) {
    install.packages("BiocManager")
}

BiocManager::install("chevreulPlot")

1.2 Required knowledge

The chevreulPlot package is designed for single-cell RNA sequencing data. The functions included within this package are derived from other packages that have implemented the infrastructure needed for RNA-seq data processing and analysis. Packages that have been instrumental in the development of chevreulPlot include, Biocpkg("SummarizedExperiment") and Biocpkg("scater").

1.3 Asking for help

R and Bioconductor have a steep learning curve so it is critical to learn where to ask for help. The Bioconductor support site is the main resource for getting help: remember to use the chevreulPlot tag and check the older posts.

2 Quick start to using chevreulPlot

The chevreulPlot package contains functions to preprocess, cluster, visualize, and perform other analyses on scRNA-seq data. It also contains a shiny app for easy visualization and analysis of scRNA data.

chvereul uses SingelCellExperiment (SCE) object type (from SingleCellExperiment) to store expression and other metadata from single-cell experiments.

This package features functions capable of:

  • Performing Clustering at a range of resolutions and Dimensional reduction of Raw Sequencing Data.
  • Visualizing scRNA data using different plotting functions.
  • Integration of multiple datasets for consistent analyses.
  • Cell cycle state regression and labeling.

library("chevreulPlot")

# Load the data
data("small_example_dataset")
sessionInfo()
#> R Under development (unstable) (2025-02-19 r87757)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.2 LTS
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#> Matrix products: default
#> BLAS:   /home/biocbuild/bbs-3.21-bioc/R/lib/libRblas.so 
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0  LAPACK version 3.12.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_GB              LC_COLLATE=C              
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
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#> 
#> time zone: America/New_York
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats4    stats     graphics  grDevices utils     datasets  methods  
#> [8] base     
#> 
#> other attached packages:
#>  [1] chevreulPlot_0.99.34        chevreulProcess_0.99.27    
#>  [3] scater_1.35.1               ggplot2_3.5.1              
#>  [5] scuttle_1.17.0              SingleCellExperiment_1.29.1
#>  [7] SummarizedExperiment_1.37.0 Biobase_2.67.0             
#>  [9] GenomicRanges_1.59.1        GenomeInfoDb_1.43.4        
#> [11] IRanges_2.41.3              S4Vectors_0.45.4           
#> [13] BiocGenerics_0.53.6         generics_0.1.3             
#> [15] MatrixGenerics_1.19.1       matrixStats_1.5.0          
#> [17] BiocStyle_2.35.0           
#> 
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#>   [3] shape_1.4.6.1             magrittr_2.0.3           
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#>  [15] DelayedMatrixStats_1.29.1 RCurl_1.98-1.16          
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#>  [93] knitr_1.49                gridExtra_2.3            
#>  [95] bookdown_0.42             ProtGenerics_1.39.2      
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