SVP
This is the development version of SVP; to use it, please install the devel version of Bioconductor.
Predicting cell states and their variability in single-cell or spatial omics data
DOI: 10.18129/B9.bioc.SVP
Bioconductor version: Development (3.21)
SVP uses the distance between cells and cells, features and features, cells and features in the space of MCA to build nearest neighbor graph, then uses random walk with restart algorithm to calculate the activity score of gene sets (such as cell marker genes, kegg pathway, go ontology, gene modules, transcription factor or miRNA target sets, reactome pathway, ...), which is then further weighted using the hypergeometric test results from the original expression matrix. To detect the spatially or single cell variable gene sets or (other features) and the spatial colocalization between the features accurately, SVP provides some global and local spatial autocorrelation method to identify the spatial variable features. SVP is developed based on SingleCellExperiment class, which can be interoperable with the existing computing ecosystem.
Author: Shuangbin Xu [aut, cre] (ORCID:
Maintainer: Shuangbin Xu <xshuangbin at 163.com>
citation("SVP")):
Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("SVP")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("SVP")| SVP Vignette | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | GO, GeneExpression, GeneSetEnrichment, GeneTarget, KEGG, SingleCell, Software, Spatial, Transcription, Transcriptomics |
| Version | 0.99.4 |
| In Bioconductor since | BioC 3.21 (R-4.5) |
| License | GPL-3 |
| Depends | R (>= 4.1.0) |
| Imports | Rcpp, RcppParallel, methods, cli, dplyr, rlang, S4Vectors, SummarizedExperiment, SingleCellExperiment, SpatialExperiment, BiocGenerics, BiocParallel, fastmatch, pracma, stats, withr, Matrix, DelayedMatrixStats, deldir, utils, BiocNeighbors, ggplot2, ggstar, ggtree, ggfun |
| System Requirements | GNU make |
| URL | https://github.com/YuLab-SMU/SVP |
| Bug Reports | https://github.com/YuLab-SMU/SVP/issues |
See More
| Suggests | rmarkdown, prettydoc, broman, RSpectra, BiasedUrn, knitr, ks, igraph, testthat (>= 3.0.0), scuttle, magrittr, DropletUtils, tibble, tidyr, harmony, aplot, scales, ggsc, scatterpie, scran, scater, STexampleData, ape |
| Linking To | Rcpp, RcppArmadillo (>= 14.0), RcppParallel, RcppEigen, dqrng |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | SVP_0.99.4.tar.gz |
| Windows Binary (x86_64) | SVP_0.99.4.zip (64-bit only) |
| macOS Binary (x86_64) | SVP_0.99.4.tgz |
| macOS Binary (arm64) | SVP_0.99.4.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/SVP |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/SVP |
| Bioc Package Browser | https://code.bioconductor.org/browse/SVP/ |
| Package Short Url | https://bioconductor.org/packages/SVP/ |
| Package Downloads Report | Download Stats |