scHOT
single-cell higher order testing
Bioconductor version: 3.23 · Package version: 1.24.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
Single cell Higher Order Testing (scHOT) is an R package that facilitates testing changes in higher order structure of gene expression along either a developmental trajectory or across space. scHOT is general and modular in nature, can be run in multiple data contexts such as along a continuous trajectory, between discrete groups, and over spatial orientations; as well as accommodate any higher order measurement such as variability or correlation. scHOT meaningfully adds to first order effect testing, such as differential expression, and provides a framework for interrogating higher order interactions from single cell data.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scHOT")Details
| Maintainer | Shila Ghazanfar <shazanfar@gmail.com> |
| Author | Shila Ghazanfar [aut, cre], Yingxin Lin [aut] |
| License | GPL-3 |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | GeneExpression, RNASeq, Sequencing, SingleCell, Software, Transcriptomics |
| Package Short Url | https://bioconductor.org/packages/scHOT/ |
Citation
From within R, enter citation("scHOT"):
Shila Ghazanfar, Yingxin Lin. scHOT: single-cell higher order testing. doi:10.18129/B9.bioc.scHOT, R package version 1.24.0, https://bioconductor.org/packages/scHOT.
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 | scHOT_1.24.0.tar.gz |
| Windows binary (x86_64) | scHOT_1.24.0.zip |
| macOS binary (arm64) | scHOT_1.24.0.tgz |
| macOS binary (x86_64) | scHOT_1.24.0.tgz |
Dependencies
Depends: R (>= 4.0)
Imports: S4Vectors (>= 0.24.3), SingleCellExperiment, Matrix, SummarizedExperiment, IRanges, methods, stats, BiocParallel, reshape, ggplot2, igraph, grDevices, ggforce, graphics
Suggests: knitr, markdown, rmarkdown, scater, scattermore, scales, matrixStats, deldir