# chevreulProcess

# Basics

## Install `chevreulProcess`

`R` is an open-source statistical environment which can be easily modified to enhance its functionality via packages. chevreulProcess 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 chevreulProcess by using the following commands in your `R` session:

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

    BiocManager::install("chevreulProcess")

## Required knowledge

The chevreulProcess 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 chevreulProcess include, `Biocpkg("SummarizedExperiment")` and `Biocpkg("scater")`.

## 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 `chevreulProcess` tag and check the older posts.

# 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 4.6.0 (2026-04-24)
    #> Platform: x86_64-pc-linux-gnu
    #> Running under: Ubuntu 24.04.4 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-r0.3.26.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=en_US.UTF-8
    #>  [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_1.4.0       scater_1.40.0
    #>  [3] ggplot2_4.0.3               scuttle_1.22.0
    #>  [5] SingleCellExperiment_1.34.0 SummarizedExperiment_1.42.0
    #>  [7] Biobase_2.72.0              GenomicRanges_1.64.0
    #>  [9] Seqinfo_1.2.0               IRanges_2.46.0
    #> [11] S4Vectors_0.50.0            BiocGenerics_0.58.0
    #> [13] generics_0.1.4              MatrixGenerics_1.24.0
    #> [15] matrixStats_1.5.0           BiocStyle_2.40.0
    #>
    #> 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_2.0.5            ggbeeswarm_0.7.3
    #>   [7] GenomicFeatures_1.64.0    farver_2.1.2
    #>   [9] rmarkdown_2.31            GlobalOptions_0.1.4
    #>  [11] fs_2.1.0                  BiocIO_1.22.0
    #>  [13] vctrs_0.7.3               memoise_2.0.1
    #>  [15] Rsamtools_2.28.0          DelayedMatrixStats_1.34.0
    #>  [17] RCurl_1.98-1.18           htmltools_0.5.9
    #>  [19] S4Arrays_1.12.0           curl_7.1.0
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    #>  [27] buildtools_1.0.0          GenomicAlignments_1.48.0
    #>  [29] igraph_2.3.0              lifecycle_1.0.5
    #>  [31] pkgconfig_2.0.3           rsvd_1.0.5
    #>  [33] Matrix_1.7-5              R6_2.6.1
    #>  [35] fastmap_1.2.0             digest_0.6.39
    #>  [37] colorspace_2.1-2          AnnotationDbi_1.74.0
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    #>  [47] withr_3.0.2               S7_0.2.2
    #>  [49] BiocParallel_1.46.0       viridis_0.6.5
    #>  [51] DBI_1.3.0                 DelayedArray_0.38.1
    #>  [53] rjson_0.2.23              bluster_1.22.0
    #>  [55] tools_4.6.0               vipor_0.4.7
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    #>  [87] ProtGenerics_1.44.0       edgeR_4.10.0
    #>  [89] cmdfun_1.0.2              xfun_0.57
    #>  [91] statmod_1.5.1             stringi_1.8.7
    #>  [93] UCSC.utils_1.8.0          EnsDb.Hsapiens.v86_2.99.0
    #>  [95] lazyeval_0.2.3            yaml_2.3.12
    #>  [97] evaluate_1.0.5            codetools_0.2-20
    #>  [99] cigarillo_1.2.0           tibble_3.3.1
    #> [101] BiocManager_1.30.27       cli_3.6.6
    #> [103] jquerylib_0.1.4           Rcpp_1.1.1-1.1
    #> [105] GenomeInfoDb_1.48.0       png_0.1-9
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    #> [109] readr_2.2.0               blob_1.3.0
    #> [111] AnnotationFilter_1.36.0   scran_1.40.0
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