# Chevreul

# Basics

## 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")

## 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")`.

## 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.

# 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 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] chevreulPlot_1.4.0          chevreulProcess_1.2.0
    #>  [3] scater_1.40.0               ggplot2_4.0.3
    #>  [5] scuttle_1.22.0              SingleCellExperiment_1.34.0
    #>  [7] SummarizedExperiment_1.42.0 Biobase_2.72.0
    #>  [9] GenomicRanges_1.64.0        Seqinfo_1.2.0
    #> [11] IRanges_2.46.0              S4Vectors_0.50.0
    #> [13] BiocGenerics_0.58.0         generics_0.1.4
    #> [15] MatrixGenerics_1.24.0       matrixStats_1.5.0
    #> [17] 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           forcats_1.0.1
    #>  [19] htmltools_0.5.9           S4Arrays_1.12.0
    #>  [21] curl_7.1.0                BiocNeighbors_2.6.0
    #>  [23] SparseArray_1.12.0        sass_0.4.10
    #>  [25] bslib_0.10.0              htmlwidgets_1.6.4
    #>  [27] plotly_4.12.0             cachem_1.1.0
    #>  [29] ResidualMatrix_1.22.0     buildtools_1.0.0
    #>  [31] GenomicAlignments_1.48.0  igraph_2.3.0
    #>  [33] iterators_1.0.14          lifecycle_1.0.5
    #>  [35] pkgconfig_2.0.3           rsvd_1.0.5
    #>  [37] Matrix_1.7-5              R6_2.6.1
    #>  [39] fastmap_1.2.0             clue_0.3-68
    #>  [41] digest_0.6.39             colorspace_2.1-2
    #>  [43] patchwork_1.3.2           AnnotationDbi_1.74.0
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    #>  [47] RSQLite_2.4.6             beachmat_2.28.0
    #>  [49] httr_1.4.8                abind_1.4-8
    #>  [51] compiler_4.6.0            doParallel_1.0.17
    #>  [53] bit64_4.8.0               withr_3.0.2
    #>  [55] S7_0.2.2                  BiocParallel_1.46.0
    #>  [57] viridis_0.6.5             DBI_1.3.0
    #>  [59] DelayedArray_0.38.0       rjson_0.2.23
    #>  [61] bluster_1.22.0            tools_4.6.0
    #>  [63] vipor_0.4.7               otel_0.2.0
    #>  [65] beeswarm_0.4.0            glue_1.8.1
    #>  [67] restfulr_0.0.16           batchelor_1.28.0
    #>  [69] grid_4.6.0                cluster_2.1.8.2
    #>  [71] megadepth_1.20.0          gtable_0.3.6
    #>  [73] tzdb_0.5.0                tidyr_1.3.2
    #>  [75] ensembldb_2.36.0          data.table_1.18.2.1
    #>  [77] hms_1.1.4                 metapod_1.20.0
    #>  [79] BiocSingular_1.28.0       ScaledMatrix_1.20.0
    #>  [81] XVector_0.52.0            foreach_1.5.2
    #>  [83] stringr_1.6.0             ggrepel_0.9.8
    #>  [85] pillar_1.11.1             limma_3.68.0
    #>  [87] circlize_0.4.18           dplyr_1.2.1
    #>  [89] lattice_0.22-9            rtracklayer_1.72.0
    #>  [91] bit_4.6.0                 tidyselect_1.2.1
    #>  [93] ComplexHeatmap_2.28.0     locfit_1.5-9.12
    #>  [95] maketools_1.3.2           Biostrings_2.80.0
    #>  [97] knitr_1.51                gridExtra_2.3
    #>  [99] ProtGenerics_1.44.0       edgeR_4.10.0
    #> [101] cmdfun_1.0.2              xfun_0.57
    #> [103] statmod_1.5.1             stringi_1.8.7
    #> [105] UCSC.utils_1.8.0          EnsDb.Hsapiens.v86_2.99.0
    #> [107] lazyeval_0.2.3            yaml_2.3.12
    #> [109] evaluate_1.0.5            codetools_0.2-20
    #> [111] cigarillo_1.2.0           tibble_3.3.1
    #> [113] wiggleplotr_1.36.0        BiocManager_1.30.27
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    #> [117] Rcpp_1.1.1-1.1            GenomeInfoDb_1.48.0
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    #> [121] parallel_4.6.0            readr_2.2.0
    #> [123] blob_1.3.0                AnnotationFilter_1.36.0
    #> [125] scran_1.40.0              sparseMatrixStats_1.24.0
    #> [127] bitops_1.0-9              viridisLite_0.4.3
    #> [129] scales_1.4.0              purrr_1.2.2
    #> [131] crayon_1.5.3              GetoptLong_1.1.1
    #> [133] rlang_1.2.0               KEGGREST_1.52.0