# chevreulShiny

Kevin Stachelek1* and Bhavana Bhat1**

1University of Southern California

*kevin.stachelek@gmail.com
**bbhat@usc.edu

#### 4 March 2025

#### Package

chevreulShiny 0.99.29

# 1 Basics

## 1.1 Install `chevreulShiny`

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

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

    BiocManager::install("chevreulShiny")

## 1.2 Required knowledge

The chevreulShiny 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 chevreulShiny 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 `chevreulShiny` tag and check the older posts.

# 2 Quick start to using `chevreulShiny`

The `chevreulShiny` 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("chevreulShiny")

    # Load the data
    data("small_example_dataset")

## 2.1 Shiny app

chevreulShiny includes a shiny app for exploratory scRNA data analysis and visualization which can be accessed via

    minimalChevreulApp(small_example_dataset)

Note: the SCE object must be pre-processed and integrated (if required) prior to building the shiny app.

The app is arranged into different sections each of which performs different function. More information about individual sections of the app is provided within the “shiny app” vignette.

`R` session information.

    #> R Under development (unstable) (2025-03-02 r87868)
    #> Platform: x86_64-apple-darwin20
    #> Running under: macOS Monterey 12.7.6
    #>
    #> Matrix products: default
    #> BLAS:   /Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/lib/libRblas.0.dylib
    #> LAPACK: /Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.0
    #>
    #> locale:
    #> [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
    #>
    #> time zone: America/New_York
    #> tzcode source: internal
    #>
    #> attached base packages:
    #> [1] stats4    stats     graphics  grDevices utils     datasets  methods   base
    #>
    #> other attached packages:
    #>  [1] chevreulShiny_0.99.29       chevreulPlot_0.99.34        chevreulProcess_0.99.27     scater_1.35.3
    #>  [5] ggplot2_3.5.1               scuttle_1.17.0              shinydashboard_0.7.2        shiny_1.10.0
    #>  [9] SingleCellExperiment_1.29.1 SummarizedExperiment_1.37.0 Biobase_2.67.0              GenomicRanges_1.59.1
    #> [13] GenomeInfoDb_1.43.4         IRanges_2.41.3              S4Vectors_0.45.4            BiocGenerics_0.53.6
    #> [17] generics_0.1.3              MatrixGenerics_1.19.1       matrixStats_1.5.0           BiocStyle_2.35.0
    #>
    #> loaded via a namespace (and not attached):
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    #>   [9] lifecycle_1.0.4           edgeR_4.5.6               doParallel_1.0.17         globals_0.16.3
    #>  [13] MASS_7.3-65               lattice_0.22-6            ensembldb_2.31.0          alabaster.base_1.7.7
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    #>  [25] metapod_1.15.0            httpuv_1.6.15             EnhancedVolcano_1.25.0    DBI_1.2.3
    #>  [29] RColorBrewer_1.1-3        ResidualMatrix_1.17.0     abind_1.4-8               purrr_1.0.4
    #>  [33] ggraph_2.2.1              AnnotationFilter_1.31.0   RCurl_1.98-1.16           yulab.utils_0.2.0
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