Basics

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

BiocManager::install("chevreulProcess")

Quick start to using chevreulProcess

The chevreulProcess 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("chevreulProcess")

# Load the data
data("small_example_dataset")

R session information.

#> R version 4.5.2 (2025-10-31)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.3 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-r0.3.26.so;  LAPACK version 3.12.0
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_US.UTF-8        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            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> time zone: Etc/UTC
#> tzcode source: system (glibc)
#> 
#> attached base packages:
#> [1] stats4    stats     graphics  grDevices utils     datasets  methods  
#> [8] base     
#> 
#> other attached packages:
#>  [1] chevreulProcess_1.3.0       scater_1.39.2              
#>  [3] ggplot2_4.0.1               scuttle_1.21.0             
#>  [5] SingleCellExperiment_1.33.0 SummarizedExperiment_1.41.0
#>  [7] Biobase_2.71.0              GenomicRanges_1.63.1       
#>  [9] Seqinfo_1.1.0               IRanges_2.45.0             
#> [11] S4Vectors_0.49.0            BiocGenerics_0.57.0        
#> [13] generics_0.1.4              MatrixGenerics_1.23.0      
#> [15] matrixStats_1.5.0           BiocStyle_2.39.0           
#> 
#> loaded via a namespace (and not attached):
#>   [1] RColorBrewer_1.1-3        sys_3.4.3                
#>   [3] jsonlite_2.0.0            shape_1.4.6.1            
#>   [5] magrittr_2.0.4            ggbeeswarm_0.7.3         
#>   [7] GenomicFeatures_1.63.1    farver_2.1.2             
#>   [9] rmarkdown_2.30            GlobalOptions_0.1.3      
#>  [11] fs_1.6.6                  BiocIO_1.21.0            
#>  [13] vctrs_0.7.0               memoise_2.0.1            
#>  [15] Rsamtools_2.27.0          DelayedMatrixStats_1.33.0
#>  [17] RCurl_1.98-1.17           htmltools_0.5.9          
#>  [19] S4Arrays_1.11.1           curl_7.0.0               
#>  [21] BiocNeighbors_2.5.2       SparseArray_1.11.10      
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#>  [51] DBI_1.2.3                 DelayedArray_0.37.0      
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#>  [79] rtracklayer_1.71.3        bit_4.6.0                
#>  [81] tidyselect_1.2.1          locfit_1.5-9.12          
#>  [83] maketools_1.3.2           Biostrings_2.79.4        
#>  [85] knitr_1.51                gridExtra_2.3            
#>  [87] ProtGenerics_1.43.0       edgeR_4.9.2              
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#>  [91] statmod_1.5.1             stringi_1.8.7            
#>  [93] UCSC.utils_1.7.1          EnsDb.Hsapiens.v86_2.99.0
#>  [95] lazyeval_0.2.2            yaml_2.3.12              
#>  [97] evaluate_1.0.5            codetools_0.2-20         
#>  [99] cigarillo_1.1.0           tibble_3.3.1             
#> [101] BiocManager_1.30.27       cli_3.6.5                
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