chevreulProcess 0.99.5
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
library(chevreuldata)
chevreul_sce <- human_gene_transcript_sce()
chevreul_sce
#> class: SingleCellExperiment
#> dim: 9740 883
#> metadata(2): markers experiment
#> assays(3): counts logcounts scaledata
#> rownames(9740): 5-8S-rRNA A2M-AS1 ... HHIP-AS1 AC117490.2
#> rowData names(0):
#> colnames(883): ds20181001-0001 ds20181001-0002 ... ds20181001-1039
#> ds20181001-1040
#> colData names(49): orig.ident nCount_gene ... nFeature_transcript ident
#> reducedDimNames(2): PCA UMAP
#> mainExpName: gene
#> altExpNames(1): transcriptR session information.
#> R Under development (unstable) (2024-10-21 r87258)
#> 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
#>
#> 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] chevreuldata_0.99.16 ExperimentHub_2.15.0
#> [3] AnnotationHub_3.15.0 BiocFileCache_2.15.0
#> [5] dbplyr_2.5.0 chevreulProcess_0.99.5
#> [7] scater_1.35.0 ggplot2_3.5.1
#> [9] scuttle_1.17.0 SingleCellExperiment_1.29.1
#> [11] SummarizedExperiment_1.37.0 Biobase_2.67.0
#> [13] GenomicRanges_1.59.1 GenomeInfoDb_1.43.1
#> [15] IRanges_2.41.1 S4Vectors_0.45.2
#> [17] BiocGenerics_0.53.3 generics_0.1.3
#> [19] MatrixGenerics_1.19.0 matrixStats_1.4.1
#> [21] BiocStyle_2.35.0
#>
#> loaded via a namespace (and not attached):
#> [1] batchelor_1.23.0 BiocIO_1.17.0
#> [3] bitops_1.0-9 filelock_1.0.3
#> [5] tibble_3.2.1 EnsDb.Mmusculus.v79_2.99.0
#> [7] graph_1.85.0 XML_3.99-0.17
#> [9] lifecycle_1.0.4 edgeR_4.5.0
#> [11] globals_0.16.3 lattice_0.22-6
#> [13] ensembldb_2.31.0 magrittr_2.0.3
#> [15] limma_3.63.2 sass_0.4.9
#> [17] rmarkdown_2.29 jquerylib_0.1.4
#> [19] yaml_2.3.10 metapod_1.15.0
#> [21] EnhancedVolcano_1.25.0 cowplot_1.1.3
#> [23] DBI_1.2.3 ResidualMatrix_1.17.0
#> [25] abind_1.4-8 zlibbioc_1.53.0
#> [27] purrr_1.0.2 AnnotationFilter_1.31.0
#> [29] RCurl_1.98-1.16 rappdirs_0.3.3
#> [31] circlize_0.4.16 GenomeInfoDbData_1.2.13
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#> [41] DelayedMatrixStats_1.29.0 codetools_0.2-20
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#> [45] shape_1.4.6.1 UCSC.utils_1.3.0
#> [47] ScaledMatrix_1.15.0 viridis_0.6.5
#> [49] GenomicAlignments_1.43.0 jsonlite_1.8.9
#> [51] BiocNeighbors_2.1.0 tools_4.5.0
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#> [55] gridExtra_2.3 SparseArray_1.7.2
#> [57] xfun_0.49 dplyr_1.1.4
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#> [79] htmltools_0.5.8.1 bookdown_0.41
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#> [85] harmony_1.2.1 scran_1.35.0
#> [87] knitr_1.49 tzdb_0.4.0
#> [89] rjson_0.2.23 curl_6.0.1
#> [91] cachem_1.1.0 GlobalOptions_0.1.2
#> [93] stringr_1.5.1 BiocVersion_3.21.1
#> [95] parallel_4.5.0 vipor_0.4.7
#> [97] AnnotationDbi_1.69.0 restfulr_0.0.15
#> [99] pillar_1.9.0 grid_4.5.0
#> [101] vctrs_0.6.5 BiocSingular_1.23.0
#> [103] EnsDb.Hsapiens.v86_2.99.0 beachmat_2.23.1
#> [105] xtable_1.8-4 cluster_2.1.6
#> [107] beeswarm_0.4.0 Rgraphviz_2.51.0
#> [109] evaluate_1.0.1 KEGGgraph_1.67.0
#> [111] readr_2.1.5 GenomicFeatures_1.59.1
#> [113] locfit_1.5-9.10 cli_3.6.3
#> [115] compiler_4.5.0 Rsamtools_2.23.0
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#> [121] ggbeeswarm_0.7.2 stringi_1.8.4
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#> [129] hms_1.1.3 sparseMatrixStats_1.19.0
#> [131] bit64_4.5.2 future_1.34.0
#> [133] KEGGREST_1.47.0 statmod_1.5.0
#> [135] igraph_2.1.1 memoise_2.0.1
#> [137] bslib_0.8.0 bit_4.5.0
#> [139] EnrichmentBrowser_2.37.0