chevreulProcess 1.3.0
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 Under development (unstable) (2025-10-20 r88955)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.3 LTS
#>
#> Matrix products: default
#> BLAS: /home/biocbuild/bbs-3.23-bioc/R/lib/libRblas.so
#> LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0 LAPACK version 3.12.0
#>
#> locale:
#> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=en_GB LC_COLLATE=C
#> [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: America/New_York
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats4 stats graphics grDevices utils datasets methods
#> [8] base
#>
#> other attached packages:
#> [1] chevreulProcess_1.3.0 scater_1.39.0
#> [3] ggplot2_4.0.0 scuttle_1.21.0
#> [5] SingleCellExperiment_1.33.0 SummarizedExperiment_1.41.0
#> [7] Biobase_2.71.0 GenomicRanges_1.63.0
#> [9] Seqinfo_1.1.0 IRanges_2.45.0
#> [11] S4Vectors_0.49.0 BiocGenerics_0.57.0
#> [13] generics_0.1.4 MatrixGenerics_1.23.0
#> [15] matrixStats_1.5.0 BiocStyle_2.39.0
#>
#> loaded via a namespace (and not attached):
#> [1] RColorBrewer_1.1-3 jsonlite_2.0.0
#> [3] shape_1.4.6.1 magrittr_2.0.4
#> [5] ggbeeswarm_0.7.2 GenomicFeatures_1.63.1
#> [7] farver_2.1.2 rmarkdown_2.30
#> [9] GlobalOptions_0.1.2 fs_1.6.6
#> [11] BiocIO_1.21.0 vctrs_0.6.5
#> [13] memoise_2.0.1 Rsamtools_2.27.0
#> [15] DelayedMatrixStats_1.33.0 RCurl_1.98-1.17
#> [17] htmltools_0.5.8.1 S4Arrays_1.11.0
#> [19] curl_7.0.0 BiocNeighbors_2.5.0
#> [21] SparseArray_1.11.1 sass_0.4.10
#> [23] bslib_0.9.0 cachem_1.1.0
#> [25] ResidualMatrix_1.21.0 GenomicAlignments_1.47.0
#> [27] igraph_2.2.1 lifecycle_1.0.4
#> [29] pkgconfig_2.0.3 rsvd_1.0.5
#> [31] Matrix_1.7-4 R6_2.6.1
#> [33] fastmap_1.2.0 digest_0.6.37
#> [35] colorspace_2.1-2 AnnotationDbi_1.73.0
#> [37] dqrng_0.4.1 irlba_2.3.5.1
#> [39] RSQLite_2.4.3 beachmat_2.27.0
#> [41] httr_1.4.7 abind_1.4-8
#> [43] compiler_4.6.0 bit64_4.6.0-1
#> [45] withr_3.0.2 S7_0.2.0
#> [47] BiocParallel_1.45.0 viridis_0.6.5
#> [49] DBI_1.2.3 DelayedArray_0.37.0
#> [51] rjson_0.2.23 bluster_1.21.0
#> [53] tools_4.6.0 vipor_0.4.7
#> [55] beeswarm_0.4.0 glue_1.8.0
#> [57] restfulr_0.0.16 batchelor_1.27.0
#> [59] grid_4.6.0 cluster_2.1.8.1
#> [61] megadepth_1.21.0 gtable_0.3.6
#> [63] tzdb_0.5.0 ensembldb_2.35.0
#> [65] hms_1.1.4 metapod_1.19.0
#> [67] BiocSingular_1.27.0 ScaledMatrix_1.19.0
#> [69] XVector_0.51.0 stringr_1.6.0
#> [71] ggrepel_0.9.6 pillar_1.11.1
#> [73] limma_3.67.0 circlize_0.4.16
#> [75] dplyr_1.1.4 lattice_0.22-7
#> [77] rtracklayer_1.71.0 bit_4.6.0
#> [79] tidyselect_1.2.1 locfit_1.5-9.12
#> [81] Biostrings_2.79.1 knitr_1.50
#> [83] gridExtra_2.3 bookdown_0.45
#> [85] ProtGenerics_1.43.0 edgeR_4.9.0
#> [87] cmdfun_1.0.2 xfun_0.54
#> [89] statmod_1.5.1 stringi_1.8.7
#> [91] UCSC.utils_1.7.0 EnsDb.Hsapiens.v86_2.99.0
#> [93] lazyeval_0.2.2 yaml_2.3.10
#> [95] evaluate_1.0.5 codetools_0.2-20
#> [97] cigarillo_1.1.0 tibble_3.3.0
#> [99] BiocManager_1.30.26 cli_3.6.5
#> [101] jquerylib_0.1.4 dichromat_2.0-0.1
#> [103] Rcpp_1.1.0 GenomeInfoDb_1.47.0
#> [105] png_0.1-8 XML_3.99-0.19
#> [107] parallel_4.6.0 readr_2.1.5
#> [109] blob_1.2.4 AnnotationFilter_1.35.0
#> [111] scran_1.39.0 sparseMatrixStats_1.23.0
#> [113] bitops_1.0-9 viridisLite_0.4.2
#> [115] scales_1.4.0 purrr_1.2.0
#> [117] crayon_1.5.3 rlang_1.1.6
#> [119] KEGGREST_1.51.0