scDesign3
A unified framework of realistic in silico data generation and statistical model inference for single-cell and spatial omics
Bioconductor version: 3.23 · Package version: 1.10.0
We present a statistical simulator, scDesign3, to generate realistic single-cell and spatial omics data, including various cell states, experimental designs, and feature modalities, by learning interpretable parameters from real data. Using a unified probabilistic model for single-cell and spatial omics data, scDesign3 infers biologically meaningful parameters; assesses the goodness-of-fit of inferred cell clusters, trajectories, and spatial locations; and generates in silico negative and positive controls for benchmarking computational tools.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scDesign3") Details
| Maintainer | Dongyuan Song <dongyuansong@ucla.edu> |
| Author | Dongyuan Song [aut, cre] (ORCID: <https://orcid.org/0000-0003-1114-1215>), Qingyang Wang [aut] (ORCID: <https://orcid.org/0000-0002-1051-609X>), Chenxin Jiang [aut] (ORCID: <https://orcid.org/0009-0005-7369-4116>) |
| License | MIT + file LICENSE |
| URL | https://github.com/SONGDONGYUAN1994/scDesign3 |
| Bug Reports | https://github.com/SONGDONGYUAN1994/scDesign3/issues |
| Downloads rank | 245 |
| Source branch | RELEASE_3_23 |
| biocViews | GeneExpression, Sequencing, SingleCell, Software, Spatial |
Documentation
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Dependencies
Depends: R (>= 4.3.0)
Imports: dplyr, tibble, stats, methods, mgcv, gamlss, gamlss.dist, SummarizedExperiment, SingleCellExperiment, mclust, mvtnorm, parallel, pbmcapply, umap, ggplot2, irlba, viridis, BiocParallel, matrixStats, Matrix, sparseMVN, coop
Suggests: mvnfast, igraph, rvinecopulib, knitr, rmarkdown, testthat (>= 3.0.0), RefManageR, sessioninfo, BiocStyle