chevreulProcess
Kevin Stachelek
University of Southern Californiakevin.stachelek@gmail.com
Bhavana Bhat
University of Southern Californiabbhat@usc.edu
27 December 2024
Source:vignettes/chevreulProcess.Rmd
chevreulProcess.RmdBasics
Install chevreulProcess
R 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")Required knowledge
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").
Asking for help
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.
Quick start to using chevreulProcess
The 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:
- Performing Clustering at a range of resolutions and Dimensional reduction of Raw Sequencing Data.
- Visualizing scRNA data using different plotting functions.
- Integration of multiple datasets for consistent analyses.
- Cell cycle state regression and labeling.
library("chevreulProcess")
#> Error in get(paste0(generic, ".", class), envir = get_method_env()) :
#> object 'type_sum.accel' not found
# 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 transcriptR session information.
#> R version 4.4.2 (2024-10-31)
#> Platform: x86_64-pc-linux-gnu
#> Running under: Ubuntu 24.04.1 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=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
#> [4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
#> [7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
#> [10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
#>
#> time zone: UTC
#> 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_2.14.0
#> [3] AnnotationHub_3.14.0 BiocFileCache_2.14.0
#> [5] dbplyr_2.5.0 chevreulProcess_0.99.23
#> [7] scater_1.34.0 ggplot2_3.5.1
#> [9] scuttle_1.16.0 SingleCellExperiment_1.28.1
#> [11] SummarizedExperiment_1.36.0 Biobase_2.66.0
#> [13] GenomicRanges_1.58.0 GenomeInfoDb_1.42.1
#> [15] IRanges_2.40.1 S4Vectors_0.44.0
#> [17] BiocGenerics_0.52.0 MatrixGenerics_1.18.0
#> [19] matrixStats_1.4.1 BiocStyle_2.34.0
#>
#> 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_1.58.0 rmarkdown_2.29
#> [7] GlobalOptions_0.1.2 fs_1.6.5
#> [9] BiocIO_1.16.0 zlibbioc_1.52.0
#> [11] ragg_1.3.3 vctrs_0.6.5
#> [13] memoise_2.0.1 Rsamtools_2.22.0
#> [15] DelayedMatrixStats_1.28.0 RCurl_1.98-1.16
#> [17] htmltools_0.5.8.1 S4Arrays_1.6.0
#> [19] curl_6.0.1 BiocNeighbors_2.0.1
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#> [25] cachem_1.1.0 ResidualMatrix_1.16.0
#> [27] GenomicAlignments_1.42.0 igraph_2.1.2
#> [29] mime_0.12 lifecycle_1.0.4
#> [31] pkgconfig_2.0.3 rsvd_1.0.5
#> [33] Matrix_1.7-1 R6_2.5.1
#> [35] fastmap_1.2.0 GenomeInfoDbData_1.2.13
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#> [93] edgeR_4.4.1 cmdfun_1.0.2
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