chevreulProcess 1.2.0
chevreulProcessR 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")
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").
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.
chevreulProcessThe 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:
library("chevreulProcess")
# Load the data
data("small_example_dataset")R session information.
#> R version 4.5.1 Patched (2025-08-23 r88802)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.3 LTS
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#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0  LAPACK version 3.12.0
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#> attached base packages:
#> [1] stats4    stats     graphics  grDevices utils     datasets  methods  
#> [8] base     
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#> other attached packages:
#>  [1] chevreulProcess_1.2.0       scater_1.38.0              
#>  [3] ggplot2_4.0.0               scuttle_1.20.0             
#>  [5] SingleCellExperiment_1.32.0 SummarizedExperiment_1.40.0
#>  [7] Biobase_2.70.0              GenomicRanges_1.62.0       
#>  [9] Seqinfo_1.0.0               IRanges_2.44.0             
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#>  [15] DelayedMatrixStats_1.32.0 RCurl_1.98-1.17          
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