PIUMA
Phenotypes Identification Using Mapper from topological data Analysis
Bioconductor version: 3.23 · Package version: 1.8.0
The PIUMA package offers a tidy pipeline of Topological Data Analysis frameworks to identify and characterize communities in high and heterogeneous dimensional data.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("PIUMA")Details
| Maintainer | Mattia Chiesa <mattia.chiesa@cardiologicomonzino.it> |
| Author | Mattia Chiesa [aut, cre] (ORCID: <https://orcid.org/0000-0001-7427-9954>), Arianna Dagliati [aut] (ORCID: <https://orcid.org/0000-0002-5041-0409>), Alessia Gerbasi [aut] (ORCID: <https://orcid.org/0000-0003-4501-1777>), Giuseppe Albi [aut], Laura Ballarini [aut], Luca Piacentini [aut] (ORCID: <https://orcid.org/0000-0003-1022-4481>), Carlo Leonardi [aut] (ORCID: <https://orcid.org/0000-0001-5348-8300>) |
| License | GPL-3 + file LICENSE |
| URL | https://github.com/BioinfoMonzino/PIUMA |
| Bug Reports | https://github.com/BioinfoMonzino/PIUMA/issues |
| Downloads rank | 173 |
| Source branch | RELEASE_3_23 |
| biocViews | Classification, Clustering, DimensionReduction, GraphAndNetwork, Network, Software |
Documentation
- The PIUMA package - Phenotypes Identification Using Mapper from topological data Analysis
- Topology-based Clustering in Seurat
Download
Dependencies
Depends: R (>= 4.3)
Imports: Hmisc, igraph, patchwork, scales, utils, cluster, umap, tsne, kernlab, vegan, dbscan, grDevices, stats, methods, SummarizedExperiment, ggplot2
Suggests: BiocStyle, testthat, knitr, rmarkdown, Seurat, SingleCellExperiment, aricode, mclust, viridis, magick, ggrepel, dplyr