chevreulPlotR is an open-source statistical environment which can be
easily modified to enhance its functionality via packages. chevreulPlot
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
chevreulPlot
by using the following commands in your R session:
The chevreulPlot
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
chevreulPlot
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
chevreulPlot tag and check the older
posts.
chevreulPlotThe chevreulPlot 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:
sessionInfo()
#> R version 4.6.0 (2026-04-24)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.4 LTS
#>
#> Matrix products: default
#> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so; LAPACK version 3.12.0
#>
#> locale:
#> [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
#> [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
#> [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: Etc/UTC
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats4 stats graphics grDevices utils datasets methods
#> [8] base
#>
#> other attached packages:
#> [1] chevreulPlot_1.5.0 chevreulProcess_1.5.0
#> [3] scater_1.41.1 ggplot2_4.0.3
#> [5] scuttle_1.23.1 SingleCellExperiment_1.35.1
#> [7] SummarizedExperiment_1.43.0 Biobase_2.73.1
#> [9] GenomicRanges_1.65.0 Seqinfo_1.3.0
#> [11] IRanges_2.47.1 S4Vectors_0.51.3
#> [13] BiocGenerics_0.59.6 generics_0.1.4
#> [15] MatrixGenerics_1.25.0 matrixStats_1.5.0
#> [17] BiocStyle_2.41.0
#>
#> loaded via a namespace (and not attached):
#> [1] RColorBrewer_1.1-3 sys_3.4.3
#> [3] jsonlite_2.0.0 shape_1.4.6.1
#> [5] magrittr_2.0.5 ggbeeswarm_0.7.3
#> [7] GenomicFeatures_1.65.0 farver_2.1.2
#> [9] rmarkdown_2.31 GlobalOptions_0.1.4
#> [11] fs_2.1.0 BiocIO_1.23.3
#> [13] vctrs_0.7.3 memoise_2.0.1
#> [15] Rsamtools_2.29.0 DelayedMatrixStats_1.35.0
#> [17] RCurl_1.98-1.18 forcats_1.0.1
#> [19] htmltools_0.5.9 S4Arrays_1.13.0
#> [21] BiocBaseUtils_1.15.1 curl_7.1.0
#> [23] BiocNeighbors_2.7.2 SparseArray_1.13.2
#> [25] sass_0.4.10 bslib_0.11.0
#> [27] htmlwidgets_1.6.4 plotly_4.12.0
#> [29] cachem_1.1.0 ResidualMatrix_1.23.0
#> [31] buildtools_1.0.0 GenomicAlignments_1.49.0
#> [33] igraph_2.3.1 iterators_1.0.14
#> [35] lifecycle_1.0.5 pkgconfig_2.0.3
#> [37] rsvd_1.0.5 Matrix_1.7-5
#> [39] R6_2.6.1 fastmap_1.2.0
#> [41] clue_0.3-68 digest_0.6.39
#> [43] colorspace_2.1-2 patchwork_1.3.2
#> [45] AnnotationDbi_1.75.0 dqrng_0.4.1
#> [47] irlba_2.3.7 RSQLite_3.53.1
#> [49] beachmat_2.29.0 httr_1.4.8
#> [51] abind_1.4-8 compiler_4.6.0
#> [53] doParallel_1.0.17 bit64_4.8.2
#> [55] withr_3.0.2 S7_0.2.2
#> [57] BiocParallel_1.47.0 viridis_0.6.5
#> [59] DBI_1.3.0 DelayedArray_0.39.3
#> [61] rjson_0.2.23 bluster_1.23.0
#> [63] tools_4.6.0 vipor_0.4.7
#> [65] otel_0.2.0 beeswarm_0.4.0
#> [67] glue_1.8.1 restfulr_0.0.16
#> [69] batchelor_1.29.0 grid_4.6.0
#> [71] cluster_2.1.8.2 megadepth_1.23.0
#> [73] gtable_0.3.6 tzdb_0.5.0
#> [75] tidyr_1.3.2 ensembldb_2.37.1
#> [77] data.table_1.18.4 hms_1.1.4
#> [79] metapod_1.21.0 BiocSingular_1.29.0
#> [81] ScaledMatrix_1.21.0 XVector_0.53.0
#> [83] foreach_1.5.2 stringr_1.6.0
#> [85] ggrepel_0.9.8 pillar_1.11.1
#> [87] limma_3.69.1 circlize_0.4.18
#> [89] dplyr_1.2.1 lattice_0.22-9
#> [91] rtracklayer_1.73.0 bit_4.6.0
#> [93] tidyselect_1.2.1 ComplexHeatmap_2.29.0
#> [95] locfit_1.5-9.12 maketools_1.3.2
#> [97] Biostrings_2.81.2 knitr_1.51
#> [99] gridExtra_2.3 ProtGenerics_1.45.0
#> [101] edgeR_4.11.1 cmdfun_1.0.2
#> [103] xfun_0.57 statmod_1.5.2
#> [105] stringi_1.8.7 UCSC.utils_1.9.0
#> [107] EnsDb.Hsapiens.v86_2.99.0 lazyeval_0.2.3
#> [109] yaml_2.3.12 evaluate_1.0.5
#> [111] codetools_0.2-20 cigarillo_1.3.0
#> [113] tibble_3.3.1 wiggleplotr_1.37.0
#> [115] BiocManager_1.30.27 cli_3.6.6
#> [117] jquerylib_0.1.4 Rcpp_1.1.1-1.1
#> [119] GenomeInfoDb_1.49.1 png_0.1-9
#> [121] XML_3.99-0.23 parallel_4.6.0
#> [123] readr_2.2.0 blob_1.3.0
#> [125] AnnotationFilter_1.37.0 scran_1.41.1
#> [127] sparseMatrixStats_1.25.0 bitops_1.0-9
#> [129] viridisLite_0.4.3 scales_1.4.0
#> [131] purrr_1.2.2 crayon_1.5.3
#> [133] GetoptLong_1.1.1 rlang_1.2.0
#> [135] KEGGREST_1.53.0