chevreulShiny (original) (raw)
Basics
Install chevreulShiny
R is an open-source statistical environment which can be easily modified to enhance its functionality via packages. chevreulShiny is a Rpackage available via the Bioconductor repository for packages. R can be installed on any operating system fromCRAN 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")
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").
Asking for help
R and Bioconductor have a steep learning curve so it is critical to learn where to ask for help. TheBioconductor support site is the main resource for getting help: remember to use the chevreulShiny tag and checkthe older posts.
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")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 version 4.5.0 RC (2025-04-04 r88126)
#> 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
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#> locale:
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#> time zone: America/New_York
#> tzcode source: system (glibc)
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#> attached base packages:
#> [1] stats4 stats graphics grDevices utils datasets methods base
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#> other attached packages:
#> [1] chevreulShiny_1.0.0 chevreulPlot_1.0.0 chevreulProcess_1.0.0 scater_1.36.0
#> [5] ggplot2_3.5.2 scuttle_1.18.0 shinydashboard_0.7.2 shiny_1.10.0
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