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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

MaintainerDongyuan Song <dongyuansong@ucla.edu>
AuthorDongyuan 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>)
LicenseMIT + file LICENSE
URLhttps://github.com/SONGDONGYUAN1994/scDesign3
Bug Reportshttps://github.com/SONGDONGYUAN1994/scDesign3/issues
Downloads rank245
Source branchRELEASE_3_23
biocViewsGeneExpression, 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