scvi-tools is an element of the scverse toolchest for single-cell omics data analysis.
The scviR package is a very elementary approach to interfacing between R, Bioconductor and scvi-tools. The long-term plan is to illustrate several aspects of variational inference (VI) applied to single cell genomics in a way that is convenient for Bioconductor users.
The package makes use of SingleCellExperiment and anndata representations of single-cell genomic assays.
Several points should be kept in mind when using this package:
As of May 2025, use BiocManager to install scviR in R 4.5.0 or above:
BiocManager::install("vjcitn/scviR")Be sure the remotes package has been installed. If you are working at a slow
internet connection, it may be useful to set options(timeout=3600) when running
functions
getCh12AllSce() (74 MB will be retrieved and cached)getCh12Sce() (58 MB will be retrieved and cached)getTotalVINormalized5k10k() (191 MB will be retrieved and cached)## R version 4.6.0 Patched (2026-04-24 r89963)
## Platform: aarch64-apple-darwin23
## Running under: macOS Tahoe 26.3.1
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## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.6/Resources/lib/libRlapack.dylib; LAPACK version 3.12.1
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## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
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## time zone: America/New_York
## tzcode source: internal
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## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
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## other attached packages:
## [1] scviR_1.12.0 shiny_1.13.0
## [3] basilisk_1.24.0 reticulate_1.46.0
## [5] scater_1.40.0 ggplot2_4.0.3
## [7] scuttle_1.22.0 SingleCellExperiment_1.34.0
## [9] SummarizedExperiment_1.42.0 Biobase_2.72.0
## [11] GenomicRanges_1.64.0 Seqinfo_1.2.0
## [13] IRanges_2.46.0 S4Vectors_0.50.0
## [15] BiocGenerics_0.58.0 generics_0.1.4
## [17] MatrixGenerics_1.24.0 matrixStats_1.5.0
## [19] BiocStyle_2.40.0
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## loaded via a namespace (and not attached):
## [1] DBI_1.3.0 gridExtra_2.3 httr2_1.2.2
## [4] rlang_1.2.0 magrittr_2.0.5 otel_0.2.0
## [7] compiler_4.6.0 RSQLite_2.4.6 mgcv_1.9-4
## [10] dir.expiry_1.20.0 png_0.1-9 vctrs_0.7.3
## [13] pkgconfig_2.0.3 fastmap_1.2.0 magick_2.9.1
## [16] dbplyr_2.5.2 XVector_0.52.0 labeling_0.4.3
## [19] promises_1.5.0 rmarkdown_2.31 ggbeeswarm_0.7.3
## [22] tinytex_0.59 purrr_1.2.2 bit_4.6.0
## [25] xfun_0.57 cachem_1.1.0 beachmat_2.28.0
## [28] jsonlite_2.0.0 blob_1.3.0 later_1.4.8
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## [34] parallel_4.6.0 R6_2.6.1 bslib_0.10.0
## [37] RColorBrewer_1.1-3 limma_3.68.0 jquerylib_0.1.4
## [40] Rcpp_1.1.1-1.1 bookdown_0.46 knitr_1.51
## [43] splines_4.6.0 httpuv_1.6.17 Matrix_1.7-5
## [46] tidyselect_1.2.1 dichromat_2.0-0.1 abind_1.4-8
## [49] yaml_2.3.12 viridis_0.6.5 codetools_0.2-20
## [52] curl_7.1.0 lattice_0.22-9 tibble_3.3.1
## [55] withr_3.0.2 S7_0.2.2 evaluate_1.0.5
## [58] BiocFileCache_3.2.0 pillar_1.11.1 BiocManager_1.30.27
## [61] filelock_1.0.3 scales_1.4.0 xtable_1.8-8
## [64] glue_1.8.1 pheatmap_1.0.13 tools_4.6.0
## [67] BiocNeighbors_2.6.0 ScaledMatrix_1.20.0 cowplot_1.2.0
## [70] grid_4.6.0 nlme_3.1-169 beeswarm_0.4.0
## [73] BiocSingular_1.28.0 vipor_0.4.7 cli_3.6.6
## [76] rsvd_1.0.5 rappdirs_0.3.4 S4Arrays_1.12.0
## [79] viridisLite_0.4.3 dplyr_1.2.1 gtable_0.3.6
## [82] sass_0.4.10 digest_0.6.39 SparseArray_1.12.0
## [85] ggrepel_0.9.8 farver_2.1.2 memoise_2.0.1
## [88] htmltools_0.5.9 lifecycle_1.0.5 statmod_1.5.1
## [91] mime_0.13 bit64_4.8.0