SETA
Single Cell Ecological Taxonomic Analysis
Bioconductor version: 3.23 · Package version: 1.2.0
Tools for compositional and other sample-level ecological analyses and visualizations tailored for single-cell RNA-seq data. SETA includes functions for taxonomizing celltypes, normalizing data, performing statistical tests, and visualizing results. Several tutorials are included to guide users and introduce them to key concepts. SETA is meant to teach users about statistical concepts underlying ecological analysis methods so they can apply them to their own single-cell data.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SETA") Details
| Maintainer | Kyle Kimler <kkimler@broadinstitute.org> |
| Author | Kyle Kimler [aut, cre] (ORCID: <https://orcid.org/0000-0003-4735-9064>), Marc Elosua-Bayes [aut] |
| License | MIT + file LICENSE |
| URL | https://github.com/kkimler/SETA |
| Bug Reports | https://github.com/kkimler/SETA/issues |
| Downloads rank | 125 |
| Source branch | RELEASE_3_23 |
| biocViews | DataRepresentation, DimensionReduction, GeneExpression, Normalization, RNASeq, SingleCell, Software, StatisticalMethod, SystemsBiology, Transcriptomics, Visualization |
Documentation
- Comparing samples with SETA
- Introduction to SETA ecological transforms and sample-level latent spaces
- Multi-Resolution Compositional Analysis in scRNA-seq: Reference Frames with SETA
Download
Dependencies
Depends: R (>= 4.5.0)
Imports: dplyr, MASS, Matrix, SingleCellExperiment (>= 1.30.1), stats, tidygraph, rlang, utils
Suggests: BiocStyle, caret, glmnet, corrplot, ggplot2, ggraph, knitr, methods, patchwork, reshape2, rmarkdown, SeuratObject, Seurat, SummarizedExperiment, TabulaMurisSenisData, tidyr, tidytext, testthat (>= 3.0.0)