chevreulPlot 0.99.24
chevreulPlot
R
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:
if (!requireNamespace("BiocManager", quietly = TRUE)) {
install.packages("BiocManager")
}
BiocManager::install("chevreulPlot")
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.
chevreulPlot
The 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:
library("chevreulPlot")
# Load the data
library(chevreuldata)
chevreul_sce <- human_gene_transcript_sce()
chevreul_sce
#> class: SingleCellExperiment
#> dim: 56267 794
#> metadata(4): merge.info pca.info experiment markers
#> assays(3): reconstructed counts logcounts
#> rownames(56267): 5-8S-rRNA 5S-rRNA ... ZZEF1 ZZZ3
#> rowData names(1): rotation
#> colnames(794): hs20151130-SC1-26 hs20151130-SC1-28 ...
#> 20200312-DS-dissected-81 20200312-DS-dissected-83
#> colData names(33): batch Sequencing_Run ... gene_snn_res.0.8
#> gene_snn_res.1
#> reducedDimNames(3): corrected TSNE UMAP
#> mainExpName: integrated
#> altExpNames(2): gene transcript
sessionInfo()
#> 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_0.99.25 ExperimentHub_2.15.0
#> [3] AnnotationHub_3.15.0 BiocFileCache_2.15.0
#> [5] dbplyr_2.5.0 chevreulPlot_0.99.24
#> [7] chevreulProcess_0.99.23 scater_1.35.0
#> [9] ggplot2_3.5.1 scuttle_1.17.0
#> [11] SingleCellExperiment_1.29.1 SummarizedExperiment_1.37.0
#> [13] Biobase_2.67.0 GenomicRanges_1.59.1
#> [15] GenomeInfoDb_1.43.2 IRanges_2.41.2
#> [17] S4Vectors_0.45.2 BiocGenerics_0.53.3
#> [19] generics_0.1.3 MatrixGenerics_1.19.0
#> [21] matrixStats_1.4.1 BiocStyle_2.35.0
#>
#> loaded via a namespace (and not attached):
#> [1] batchelor_1.23.0 BiocIO_1.17.1
#> [3] bitops_1.0-9 filelock_1.0.3
#> [5] tibble_3.2.1 XML_3.99-0.17
#> [7] lifecycle_1.0.4 edgeR_4.5.1
#> [9] doParallel_1.0.17 lattice_0.22-6
#> [11] ensembldb_2.31.0 magrittr_2.0.3
#> [13] limma_3.63.2 plotly_4.10.4
#> [15] sass_0.4.9 rmarkdown_2.29
#> [17] jquerylib_0.1.4 yaml_2.3.10
#> [19] metapod_1.15.0 DBI_1.2.3
#> [21] RColorBrewer_1.1-3 ResidualMatrix_1.17.0
#> [23] abind_1.4-8 zlibbioc_1.53.0
#> [25] purrr_1.0.2 AnnotationFilter_1.31.0
#> [27] RCurl_1.98-1.16 rappdirs_0.3.3
#> [29] circlize_0.4.16 GenomeInfoDbData_1.2.13
#> [31] ggrepel_0.9.6 irlba_2.3.5.1
#> [33] megadepth_1.17.0 cmdfun_1.0.2
#> [35] dqrng_0.4.1 DelayedMatrixStats_1.29.0
#> [37] codetools_0.2-20 DelayedArray_0.33.3
#> [39] tidyselect_1.2.1 shape_1.4.6.1
#> [41] UCSC.utils_1.3.0 farver_2.1.2
#> [43] wiggleplotr_1.31.0 ScaledMatrix_1.15.0
#> [45] viridis_0.6.5 GenomicAlignments_1.43.0
#> [47] jsonlite_1.8.9 GetoptLong_1.0.5
#> [49] BiocNeighbors_2.1.2 iterators_1.0.14
#> [51] foreach_1.5.2 tools_4.5.0
#> [53] Rcpp_1.0.13-1 glue_1.8.0
#> [55] gridExtra_2.3 SparseArray_1.7.2
#> [57] xfun_0.49 dplyr_1.1.4
#> [59] withr_3.0.2 BiocManager_1.30.25
#> [61] fastmap_1.2.0 bluster_1.17.0
#> [63] fansi_1.0.6 digest_0.6.37
#> [65] rsvd_1.0.5 mime_0.12
#> [67] R6_2.5.1 colorspace_2.1-1
#> [69] RSQLite_2.3.9 tidyr_1.3.1
#> [71] utf8_1.2.4 data.table_1.16.4
#> [73] rtracklayer_1.67.0 htmlwidgets_1.6.4
#> [75] httr_1.4.7 S4Arrays_1.7.1
#> [77] pkgconfig_2.0.3 gtable_0.3.6
#> [79] blob_1.2.4 ComplexHeatmap_2.23.0
#> [81] XVector_0.47.0 htmltools_0.5.8.1
#> [83] bookdown_0.41 ProtGenerics_1.39.0
#> [85] clue_0.3-66 scales_1.3.0
#> [87] png_0.1-8 scran_1.35.0
#> [89] knitr_1.49 tzdb_0.4.0
#> [91] rjson_0.2.23 curl_6.0.1
#> [93] cachem_1.1.0 GlobalOptions_0.1.2
#> [95] stringr_1.5.1 BiocVersion_3.21.1
#> [97] parallel_4.5.0 vipor_0.4.7
#> [99] AnnotationDbi_1.69.0 restfulr_0.0.15
#> [101] pillar_1.9.0 grid_4.5.0
#> [103] vctrs_0.6.5 BiocSingular_1.23.0
#> [105] EnsDb.Hsapiens.v86_2.99.0 beachmat_2.23.4
#> [107] cluster_2.1.8 beeswarm_0.4.0
#> [109] evaluate_1.0.1 readr_2.1.5
#> [111] GenomicFeatures_1.59.1 cli_3.6.3
#> [113] locfit_1.5-9.10 compiler_4.5.0
#> [115] Rsamtools_2.23.1 rlang_1.1.4
#> [117] crayon_1.5.3 forcats_1.0.0
#> [119] fs_1.6.5 ggbeeswarm_0.7.2
#> [121] stringi_1.8.4 viridisLite_0.4.2
#> [123] BiocParallel_1.41.0 munsell_0.5.1
#> [125] Biostrings_2.75.2 lazyeval_0.2.2
#> [127] Matrix_1.7-1 hms_1.1.3
#> [129] patchwork_1.3.0 sparseMatrixStats_1.19.0
#> [131] bit64_4.5.2 KEGGREST_1.47.0
#> [133] statmod_1.5.0 igraph_2.1.2
#> [135] memoise_2.0.1 bslib_0.8.0
#> [137] bit_4.5.0.1