scTensor
Detection of cell-cell interaction from single-cell RNA-seq dataset by tensor decomposition
Bioconductor version: 3.23 · Package version: 2.22.0
The algorithm is based on the non-negative tucker decomposition (NTD2) of nnTensor.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scTensor")Details
| Maintainer | Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp> |
| Author | Koki Tsuyuzaki [aut, cre], Kozo Nishida [aut] |
| License | Artistic-2.0 |
| Downloads rank | 313 |
| Source branch | RELEASE_3_23 |
| biocViews | DimensionReduction, GeneExpression, SingleCell, Software |
Documentation
- Detection and visualization of cell-cell interactions using LRBase and scTensor
- Roadmap to prepare the input matrix for scTensor
- How to interpret the HTML report generated by cellCellReport function
- How to perform CCI simulation by cellCellSimulate function
- How to reanalyze the results of scTensor
Download
Dependencies
Depends: R (>= 4.1.0)
Imports: methods, RSQLite, igraph, S4Vectors, plotly, reactome.db, AnnotationDbi, SummarizedExperiment, SingleCellExperiment, nnTensor (>= 1.1.5), ccTensor (>= 1.0.2), rTensor (>= 1.4.8), abind, plotrix, heatmaply, tagcloud, rmarkdown, BiocStyle, knitr, AnnotationHub, MeSHDbi (>= 1.29.2), grDevices, graphics, stats, utils, outliers, Category, meshr (>= 1.99.1), GOstats, ReactomePA, DOSE, crayon, checkmate, BiocManager, visNetwork, schex, ggplot2
Suggests: testthat, LRBaseDbi, Seurat, scTGIF, Homo.sapiens