simPIC
Flexible simulation of paired-insertion counts for single-cell ATAC-sequencing data
Bioconductor version: 3.24 · Package version: 1.9.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
simPIC is a package for simulating single-cell ATAC-seq count data. It provides a user-friendly, well documented interface for data simulation. Functions are provided for parameter estimation, realistic scATAC-seq data simulation, and comparing real and simulated datasets.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("simPIC")Details
| Maintainer | Sagrika Chugh <sagrika.chugh@gmail.com> |
| Author | Sagrika Chugh [aut, cre] (<https://orcid.org/0000-0002-8050-5214>), Heejung Shim [aut], Davis McCarthy [aut] |
| License | GPL-3 |
| URL | https://github.com/sagrikachugh/simPIC |
| Bug Reports | https://github.com/sagrikachugh/simPIC/issues |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | ATACSeq, DataImport, ImmunoOncology, Sequencing, SingleCell, Software |
| Package Short Url | https://bioconductor.org/packages/simPIC/ |
Citation
From within R, enter citation("simPIC"):
Sagrika Chugh, Heejung Shim, Davis McCarthy. simPIC: Flexible simulation of paired-insertion counts for single-cell ATAC-sequencing data. doi:10.18129/B9.bioc.simPIC, R package version 1.9.0, https://bioconductor.org/packages/simPIC.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | simPIC_1.9.0.tar.gz |
| Windows binary (x86_64) | simPIC_1.9.0.zip |
| macOS binary (arm64) | simPIC_1.9.0.tgz |
| macOS binary (x86_64) | simPIC_1.9.0.tgz |
Dependencies
Depends: R (>= 4.5.0), SingleCellExperiment
Imports: BiocGenerics, checkmate (>= 2.0.0), fitdistrplus, matrixStats, actuar, Matrix, stats, SummarizedExperiment, rlang, S4Vectors, GenomeInfoDb, methods, scales, scuttle, edgeR, withr
Suggests: bluster, ggplot2 (>= 3.4.0), knitr, rmarkdown, BiocStyle, testthat (>= 3.0.0), scater, scran, magick, splatter, VariantAnnotation, IRanges, GenomicRanges, preprocessCore