| scTensor-package {scTensor} | R Documentation |
The algorithm is based on the non-negative tucker decomposition (NTD2) of nnTensor.
The DESCRIPTION file:
| Package: | scTensor |
| Type: | Package |
| Title: | Detection of cell-cell interaction from single-cell RNA-seq dataset by tensor decomposition |
| Version: | 1.2.1 |
| Authors@R: | c(person("Koki", "Tsuyuzaki", role = c("aut", "cre"), email = "k.t.the-answer@hotmail.co.jp"), person("Kozo", "Nishida", role = "aut", email = "kozo.nishida@gmail.com")) |
| Depends: | R (>= 3.5.0) |
| Imports: | methods, RSQLite, igraph, S4Vectors, plotly, reactome.db, AnnotationDbi, SummarizedExperiment, SingleCellExperiment, nnTensor, rTensor, abind, plotrix, heatmaply, tagcloud, rmarkdown, BiocStyle, knitr, AnnotationHub, MeSHDbi, grDevices, graphics, stats, utils, outliers, Category, meshr, GOstats, ReactomePA, DOSE, crayon, checkmate, BiocManager, visNetwork |
| Suggests: | testthat, LRBase.Hsa.eg.db, MeSH.Hsa.eg.db, LRBase.Mmu.eg.db, MeSH.Mmu.eg.db, LRBaseDbi, Seurat, Homo.sapiens |
| Description: | The algorithm is based on the non-negative tucker decomposition (NTD2) of nnTensor. |
| License: | Artistic-2.0 |
| biocViews: | DimensionReduction, SingleCell, Software, GeneExpression |
| VignetteBuilder: | knitr |
| git_url: | https://git.bioconductor.org/packages/scTensor |
| git_branch: | RELEASE_3_10 |
| git_last_commit: | c4b8069 |
| git_last_commit_date: | 2019-11-08 |
| Date/Publication: | 2019-11-09 |
| Author: | Koki Tsuyuzaki [aut, cre], Kozo Nishida [aut] |
| Maintainer: | Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp> |
Index of help topics:
CCSParams-class Class "CCSParams"
GermMale The matrix which is used as test data of
scTensor.
cellCellDecomp Performing scTensor
cellCellRanks Rank estimation of the CCI-tensor
cellCellReport HTML report of the result of scTensor
cellCellSetting Parameter setting for scTensor
cellCellSimulate Parameter Simulate for scTensor
convertToNCBIGeneID ID conversion function to create the input
matrix for scTensor
getParam Get a parameter
labelGermMale The vector contains the celltype information
and color scheme of GermMale
m The gene-wise mean vector of Quartz-Seq data.
newCCSParams New Params
scTensor-package Detection of cell-cell interaction from
single-cell RNA-seq dataset by tensor
decomposition
setParam Set a parameter
tsneGermMale The result of Rtsne against GermMale
v The gene-wise variance vector of Quartz-Seq
data.
NA
Maintainer: NA
GermMale,labelGermMale,
tsneGermMale,cellCellSetting,
cellCellDecomp,cellCellReport
if(interactive()){
# Package Loading
library(SingleCellExperiment)
library(LRBase.Hsa.eg.db)
# Data Loading
data(GermMale)
data(labelGermMale)
data(tsneGermMale)
# SingleCellExperiment-class
sce <- SingleCellExperiment(assays = list(counts = GermMale))
reducedDims(sce) <- SimpleList(TSNE=tsneGermMale$Y)
# Setting
cellCellSetting(sce, LRBase.Hsa.eg.db, labelGermMale, names(labelGermMale))
# Decomposition
cellCellDecomp(sce, ranks=c(4,4,5))
# Report
tmp <- tempdir()
cellCellReport(sce, reducedDimNames="TSNE", out.dir=tmp,
html.open = TRUE,
title="Cell-cell interaction within Germline, Male, GSE86146",
author="Koki Tsuyuzaki", thr=5)
}else{
ls("package:scTensor")
}