chevreulShinyR is an open-source statistical environment which can be
easily modified to enhance its functionality via packages. chevreulShiny
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
chevreulShiny
by using the following commands in your R session:
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").
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
chevreulShiny tag and check the older
posts.
chevreulShinyThe 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:
chevreulShiny includes a shiny app for exploratory scRNA data analysis and visualization which can be accessed via
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 4.4.2 (2024-10-31)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.2 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 LC_TIME=en_US.UTF-8 LC_COLLATE=C
#> [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C
#> [9] LC_ADDRESS=C LC_TELEPHONE=C 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 base
#>
#> other attached packages:
#> [1] chevreulShiny_0.99.29 chevreulPlot_0.99.34 chevreulProcess_0.99.27 scater_1.35.1
#> [5] ggplot2_3.5.1 scuttle_1.17.0 shinydashboard_0.7.2 shiny_1.10.0
#> [9] SingleCellExperiment_1.29.1 SummarizedExperiment_1.37.0 Biobase_2.67.0 GenomicRanges_1.59.1
#> [13] GenomeInfoDb_1.43.4 IRanges_2.41.3 S4Vectors_0.45.4 BiocGenerics_0.53.6
#> [17] generics_0.1.3 MatrixGenerics_1.19.1 matrixStats_1.5.0 BiocStyle_2.35.0
#>
#> loaded via a namespace (and not attached):
#> [1] later_1.4.1 batchelor_1.23.0 BiocIO_1.17.1 ggplotify_0.1.2
#> [5] bitops_1.0-9 tibble_3.2.1 polyclip_1.10-7 XML_3.99-0.18
#> [9] lifecycle_1.0.4 edgeR_4.5.4 doParallel_1.0.17 globals_0.16.3
#> [13] MASS_7.3-65 lattice_0.22-6 ensembldb_2.31.0 alabaster.base_1.7.7
#> [17] magrittr_2.0.3 limma_3.63.8 plotly_4.10.4 sass_0.4.9
#> [21] rmarkdown_2.29 jquerylib_0.1.4 yaml_2.3.10 shinyBS_0.61.1
#> [25] metapod_1.15.0 httpuv_1.6.15 EnhancedVolcano_1.25.0 DBI_1.2.3
#> [29] buildtools_1.0.0 RColorBrewer_1.1-3 ResidualMatrix_1.17.0 abind_1.4-8
#> [33] purrr_1.0.4 ggraph_2.2.1 AnnotationFilter_1.31.0 RCurl_1.98-1.16
#> [37] yulab.utils_0.2.0 rappdirs_0.3.3 tweenr_2.0.3 circlize_0.4.16
#> [41] GenomeInfoDbData_1.2.13 ggrepel_0.9.6 irlba_2.3.5.1 listenv_0.9.1
#> [45] megadepth_1.17.0 maketools_1.3.2 cmdfun_1.0.2 parallelly_1.42.0
#> [49] dqrng_0.4.1 DelayedMatrixStats_1.29.1 codetools_0.2-20 DelayedArray_0.33.6
#> [53] ggforce_0.4.2 DT_0.33 tidyselect_1.2.1 shape_1.4.6.1
#> [57] UCSC.utils_1.3.1 farver_2.1.2 rhandsontable_0.3.8 wiggleplotr_1.31.0
#> [61] ScaledMatrix_1.15.0 viridis_0.6.5 shinyWidgets_0.9.0 GenomicAlignments_1.43.0
#> [65] jsonlite_1.9.1 GetoptLong_1.0.5 BiocNeighbors_2.1.2 waiter_0.2.5
#> [69] tidygraph_1.3.1 iterators_1.0.14 foreach_1.5.2 tools_4.4.2
#> [73] Rcpp_1.0.14 glue_1.8.0 gridExtra_2.3 SparseArray_1.7.6
#> [77] xfun_0.51 dplyr_1.1.4 withr_3.0.2 BiocManager_1.30.25
#> [81] fastmap_1.2.0 clustree_0.5.1 rhdf5filters_1.19.1 bluster_1.17.0
#> [85] shinyjs_2.1.0 digest_0.6.37 rsvd_1.0.5 gridGraphics_0.5-1
#> [89] R6_2.6.1 mime_0.12 colorspace_2.1-1 RSQLite_2.3.9
#> [93] tidyr_1.3.1 data.table_1.17.0 rtracklayer_1.67.1 graphlayouts_1.2.2
#> [97] httr_1.4.7 htmlwidgets_1.6.4 S4Arrays_1.7.3 pkgconfig_2.0.3
#> [101] gtable_0.3.6 blob_1.2.4 ComplexHeatmap_2.23.0 XVector_0.47.2
#> [105] sys_3.4.3 htmltools_0.5.8.1 shinyhelper_0.3.2 ProtGenerics_1.39.2
#> [109] clue_0.3-66 scales_1.3.0 png_0.1-8 scran_1.35.0
#> [113] rstudioapi_0.17.1 knitr_1.49 tzdb_0.4.0 rjson_0.2.23
#> [117] curl_6.2.1 rhdf5_2.51.2 cachem_1.1.0 GlobalOptions_0.1.2
#> [121] stringr_1.5.1 miniUI_0.1.1.1 parallel_4.4.2 vipor_0.4.7
#> [125] AnnotationDbi_1.69.0 restfulr_0.0.15 alabaster.schemas_1.7.0 pillar_1.10.1
#> [129] grid_4.4.2 vctrs_0.6.5 promises_1.3.2 shinyFiles_0.9.3
#> [133] BiocSingular_1.23.0 EnsDb.Hsapiens.v86_2.99.0 beachmat_2.23.6 xtable_1.8-4
#> [137] cluster_2.1.8 beeswarm_0.4.0 evaluate_1.0.3 readr_2.1.5
#> [141] GenomicFeatures_1.59.1 cli_3.6.4 locfit_1.5-9.11 compiler_4.4.2
#> [145] Rsamtools_2.23.1 rlang_1.1.5 crayon_1.5.3 DataEditR_0.1.5
#> [149] forcats_1.0.0 fs_1.6.5 ggbeeswarm_0.7.2 stringi_1.8.4
#> [153] viridisLite_0.4.2 BiocParallel_1.41.2 munsell_0.5.1 Biostrings_2.75.4
#> [157] lazyeval_0.2.2 Matrix_1.7-2 hms_1.1.3 patchwork_1.3.0
#> [161] future_1.34.0 sparseMatrixStats_1.19.0 bit64_4.6.0-1 Rhdf5lib_1.29.1
#> [165] KEGGREST_1.47.0 statmod_1.5.0 igraph_2.1.4 memoise_2.0.1
#> [169] bslib_0.9.0 bit_4.5.0.1