Installations | Goal | Quick start by SingleCellExperiment objects | Preprocessing | Prepare SingleCellExperiment objects | Control data quality | Remove variables based on expression profiles | Remove samples based on expression profiles | Remove variables based on the mean read counts | Normalize data | Multifaceted sign analysis | Compute correlation matrices | Load databases | Create signs | Select signs | Create sign-by-sample matrices | Reduce dimensions of sign-by-sample matrices | Cluster cells | Use Seurat functions | Cell cycle inference using Seurat functions | Investigate significant signs | Investigate significant genes | Use Seurat function | Multifaceted analysis | Session information
Package: ASURAT 1.17.0
Keita Iida
ASURAT: Functional annotation-driven unsupervised clustering for single-cell data
ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).
Authors:
ASURAT_1.17.0.tar.gz
ASURAT_1.17.0.zip(r-4.7)ASURAT_1.17.0.zip(r-4.6)ASURAT_1.17.0.zip(r-4.5)
ASURAT_1.17.0.tgz(r-4.6-x86_64)ASURAT_1.17.0.tgz(r-4.6-arm64)ASURAT_1.17.0.tgz(r-4.5-x86_64)ASURAT_1.17.0.tgz(r-4.5-arm64)
ASURAT_1.17.0.tar.gz(r-4.7-arm64)ASURAT_1.17.0.tar.gz(r-4.7-x86_64)ASURAT_1.17.0.tar.gz(r-4.6-arm64)ASURAT_1.17.0.tar.gz(r-4.6-x86_64)
ASURAT_1.17.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ASURAT/json (API)
| # Install 'ASURAT' in R: |
| install.packages('ASURAT', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- human_COMSig_eg - A list of small Cell Ontology and MSigDB databases for human.
- human_GO_eg - A list of small Gene Ontology database for human.
- human_KEGG_eg - A list of small KEGG database for human.
- pbmc_eg - A SingleCellExperiment object made from a gene expression table.
- pbmcs_eg - A list of SingleCellExperiment objects made from sign-sample matrices.
On BioConductor:ASURAT-1.17.0(bioc 3.24)ASURAT-1.16.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
geneexpressionsinglecellsequencingclusteringgenesignalingcpp
Last updated from:35fd355722. Checks:12 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | NOTE | 261 | ||
| linux-devel-arm64 | NOTE | 361 | ||
| linux-devel-x86_64 | NOTE | 422 | ||
| source / vignettes | OK | 887 | ||
| linux-release-arm64 | NOTE | 361 | ||
| linux-release-x86_64 | NOTE | 359 | ||
| macos-release-arm64 | NOTE | 248 | ||
| macos-release-x86_64 | NOTE | 422 | ||
| macos-oldrel-arm64 | NOTE | 284 | ||
| macos-oldrel-x86_64 | NOTE | 484 | ||
| windows-devel | NOTE | 1118 | ||
| windows-release | NOTE | 1166 | ||
| windows-oldrel | NOTE | 1192 | ||
| wasm-release | OK | 225 |
Exports:add_metadatabubble_sortcluster_genesetscompute_sepI_allcompute_sepI_clusterscreate_signsmakeSignMatrixplot_dataframe3Dplot_multiheatmapsremove_samplesremove_signsremove_signs_manuallyremove_signs_redundantremove_variablesremove_variables_secondselect_signs_manuallyswap_pass
Dependencies:abindBiobaseBiocGenericscirclizeclueclustercodetoolscolorspaceComplexHeatmapcrayonDelayedArraydigestdoParallelforeachgenericsGenomicRangesGetoptLongGlobalOptionsIRangesiteratorslatticeMatrixMatrixGenericsmatrixStatsmisc3dplot3DpngRColorBrewerRcpprjsonS4ArraysS4VectorsSeqinfoshapeSingleCellExperimentSparseArraySummarizedExperimentXVector
