You can install the development version of scend from GitHub with:
if (!requireNamespace("pak")) {
install.packages("pak",
repos = sprintf(
"https://r-lib.github.io/p/pak/devel/%s/%s/%s",
.Platform$pkgType, R.Version()$os, R.Version()$arch
)
)
}
pak::pkg_install("Yunuuuu/scend")scrapper is a package provides
methods for an end-to-end analysis of a single-cell RNA-sequencing
(scRNA-seq) analysis, starting from the count matrix and finishes with
clusters, markers, and various embeddings (i.e., t-SNE and UMAP). It’s
pretty fast and memory-efficient. The package serves as a bridging tool
connecting the scrapper package with either Seurat or
SingleCellExperiment objects.
| functions | Description |
|---|---|
librarySizeFactors |
Compute library size factors |
logNormCounts |
Log-transformed normalized expression |
modelGeneVar |
Model per-gene variances in expression |
runPCA |
Principal component analysis |
runMNN |
Fast mutual nearest neighbors correction |
subSample |
Subsample cells based on their neighbors |
runTSNE |
t-stochastic neighbor embedding |
runUMAP |
uniform manifold approximation and projection |
runDiffusionMap |
diffusion map |
clusterSNNGraph |
Graph-based clustering |
subCluster |
Find subclusters |
scoreMarkers |
Score marker genes |
scoreFeatureSet |
Score feature set activity for each cell |
infercnv |
Run infercnv workflow |
scenic |
Single-Cell Regulatory Network Inference and Clustering |