Coralysis
Coralysis sensitive identification of imbalanced cell types and states in single-cell data via multi-level integration
Bioconductor version: 3.24 · Package version: 1.3.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
Coralysis is an R package featuring a multi-level integration algorithm for sensitive integration, reference-mapping, and cell-state identification in single-cell data. The multi-level integration algorithm is inspired by the process of assembling a puzzle - where one begins by grouping pieces based on low-to high-level features, such as color and shading, before looking into shape and patterns. This approach progressively blends the batch effects and separates cell types across multiple rounds of divisive clustering.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("Coralysis")Details
| Maintainer | António Sousa <aggode@utu.fi> |
| Author | António Sousa [cre, aut] (ORCID: <https://orcid.org/0000-0003-4779-6459>), Johannes Smolander [ctb, aut] (ORCID: <https://orcid.org/0000-0003-3872-9668>), Sini Junttila [aut] (ORCID: <https://orcid.org/0000-0003-3754-5584>), Laura L Elo [aut] (ORCID: <https://orcid.org/0000-0001-5648-4532>) |
| License | GPL-3 |
| URL | https://github.com/elolab/Coralysis, https://elolab.github.io/Coralysis/ |
| Bug Reports | https://github.com/elolab/Coralysis/issues |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | Annotation, BatchEffect, Classification, Clustering, DifferentialExpression, DimensionReduction, GeneExpression, Proteomics, RNASeq, SingleCell, Software, Transcriptomics |
| Package Short Url | https://bioconductor.org/packages/Coralysis/ |
Citation
From within R, enter citation("Coralysis"):
António Sousa, Johannes Smolander, Sini Junttila, Laura L Elo. Coralysis: Coralysis sensitive identification of imbalanced cell types and states in single-cell data via multi-level integration. doi:10.18129/B9.bioc.Coralysis, R package version 1.3.0, https://bioconductor.org/packages/Coralysis.
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 | Coralysis_1.3.0.tar.gz |
| Windows binary (x86_64) | Coralysis_1.3.0.zip |
| macOS binary (arm64) | Coralysis_1.3.0.tgz |
| macOS binary (x86_64) | Coralysis_1.3.0.tgz |
Dependencies
Depends: R (>= 4.2.0)
Imports: Matrix, aricode, LiblineaR, SparseM, ggplot2, umap, Rtsne, pheatmap, reshape2, dplyr, SingleCellExperiment, SummarizedExperiment, S4Vectors, methods, stats, utils, RANN, sparseMatrixStats, irlba, flexclust, scran, class, matrixStats, tidyr, cowplot, uwot, scatterpie, RColorBrewer, ggrastr, ggrepel, RSpectra, BiocParallel, withr
Suggests: knitr, rmarkdown, bluster, ComplexHeatmap, circlize, scater, viridis, scRNAseq, SingleR, MouseGastrulationData, testthat (>= 3.0.0), BiocStyle, scrapper