chevreulProcess 0.99.27
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) (2025-01-20 r87609)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.1 LTS
#>
#> 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
#>
#> 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_0.99.27 scater_1.35.1
#> [3] ggplot2_3.5.1 scuttle_1.17.0
#> [5] SingleCellExperiment_1.29.1 SummarizedExperiment_1.37.0
#> [7] Biobase_2.67.0 GenomicRanges_1.59.1
#> [9] GenomeInfoDb_1.43.4 IRanges_2.41.3
#> [11] S4Vectors_0.45.4 BiocGenerics_0.53.6
#> [13] generics_0.1.3 MatrixGenerics_1.19.1
#> [15] matrixStats_1.5.0 BiocStyle_2.35.0
#>
#> loaded via a namespace (and not attached):
#> [1] jsonlite_1.8.9 shape_1.4.6.1
#> [3] magrittr_2.0.3 ggbeeswarm_0.7.2
#> [5] GenomicFeatures_1.59.1 rmarkdown_2.29
#> [7] GlobalOptions_0.1.2 fs_1.6.5
#> [9] BiocIO_1.17.1 vctrs_0.6.5
#> [11] memoise_2.0.1 Rsamtools_2.23.1
#> [13] DelayedMatrixStats_1.29.1 RCurl_1.98-1.16
#> [15] htmltools_0.5.8.1 S4Arrays_1.7.3
#> [17] curl_6.2.0 BiocNeighbors_2.1.2
#> [19] SparseArray_1.7.5 sass_0.4.9
#> [21] bslib_0.9.0 cachem_1.1.0
#> [23] ResidualMatrix_1.17.0 GenomicAlignments_1.43.0
#> [25] igraph_2.1.4 lifecycle_1.0.4
#> [27] pkgconfig_2.0.3 rsvd_1.0.5
#> [29] Matrix_1.7-2 R6_2.6.0
#> [31] fastmap_1.2.0 GenomeInfoDbData_1.2.13
#> [33] digest_0.6.37 colorspace_2.1-1
#> [35] AnnotationDbi_1.69.0 dqrng_0.4.1
#> [37] irlba_2.3.5.1 RSQLite_2.3.9
#> [39] beachmat_2.23.6 httr_1.4.7
#> [41] abind_1.4-8 compiler_4.5.0
#> [43] bit64_4.6.0-1 withr_3.0.2
#> [45] BiocParallel_1.41.0 viridis_0.6.5
#> [47] DBI_1.2.3 DelayedArray_0.33.5
#> [49] rjson_0.2.23 bluster_1.17.0
#> [51] tools_4.5.0 vipor_0.4.7
#> [53] beeswarm_0.4.0 glue_1.8.0
#> [55] restfulr_0.0.15 batchelor_1.23.0
#> [57] grid_4.5.0 cluster_2.1.8
#> [59] megadepth_1.17.0 gtable_0.3.6
#> [61] tzdb_0.4.0 ensembldb_2.31.0
#> [63] hms_1.1.3 metapod_1.15.0
#> [65] BiocSingular_1.23.0 ScaledMatrix_1.15.0
#> [67] XVector_0.47.2 stringr_1.5.1
#> [69] ggrepel_0.9.6 pillar_1.10.1
#> [71] limma_3.63.3 circlize_0.4.16
#> [73] dplyr_1.1.4 lattice_0.22-6
#> [75] rtracklayer_1.67.0 bit_4.5.0.1
#> [77] tidyselect_1.2.1 locfit_1.5-9.11
#> [79] Biostrings_2.75.3 knitr_1.49
#> [81] gridExtra_2.3 bookdown_0.42
#> [83] ProtGenerics_1.39.2 edgeR_4.5.2
#> [85] cmdfun_1.0.2 xfun_0.50
#> [87] statmod_1.5.0 stringi_1.8.4
#> [89] UCSC.utils_1.3.1 EnsDb.Hsapiens.v86_2.99.0
#> [91] lazyeval_0.2.2 yaml_2.3.10
#> [93] evaluate_1.0.3 codetools_0.2-20
#> [95] tibble_3.2.1 BiocManager_1.30.25
#> [97] cli_3.6.3 munsell_0.5.1
#> [99] jquerylib_0.1.4 Rcpp_1.0.14
#> [101] png_0.1-8 XML_3.99-0.18
#> [103] parallel_4.5.0 readr_2.1.5
#> [105] blob_1.2.4 AnnotationFilter_1.31.0
#> [107] scran_1.35.0 sparseMatrixStats_1.19.0
#> [109] bitops_1.0-9 viridisLite_0.4.2
#> [111] scales_1.3.0 purrr_1.0.4
#> [113] crayon_1.5.3 rlang_1.1.5
#> [115] KEGGREST_1.47.0