Package: scider 1.11.0

Yunshun Chen

scider: Spatial cell-type inter-correlation by density in R

scider is an user-friendly R package providing functions to model the global density of cells in a slide of spatial transcriptomics data. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. After modelling density, the package allows for several downstream analysis, including colocalization analysis, boundary detection analysis and differential density analysis.

Authors:Mengbo Li, Ning Liu, Quoc Hoang Nguyen, Yunshun Chen

scider_1.11.0.tar.gz
scider_1.11.0.zip(r-4.7-x86_64)scider_1.11.0.zip(r-4.7-arm64)scider_1.11.0.zip(r-4.6-x86_64)scider_1.11.0.zip(r-4.6-arm64)scider_1.11.0.zip(r-4.5-x86_64)
scider_1.11.0.tar.gz(r-4.7-arm64)scider_1.11.0.tar.gz(r-4.7-x86_64)scider_1.11.0.tar.gz(r-4.6-arm64)scider_1.11.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
scider/json (API)

# Install 'scider' in R:

install.packages('scider', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/chenlaboratory/scider/issues

Pkgdown/docs site:https://chenlaboratory.github.io

Uses libs:

c++– GNU Standard C++ Library v3
openjdk– OpenJDK Java runtime, using Hotspot JIT

On BioConductor:scider-1.11.0(bioc 3.24)scider-1.10.0(bioc 3.23)

spatial transcriptomics cpp openjdk

6.60 score 12 stars 1 packages 11 scripts 380 downloads 43 exports 181 dependencies

Last updated from:7dcb837f32. Checks:1 WARNING, 9 NOTE, 1 OK, 5 FAIL. Indexed: yes.

Target	Result	Time
bioc-checks	WARNING	228
linux-devel-arm64	NOTE	422
linux-devel-x86_64	NOTE	497
source / vignettes	OK	327
linux-release-arm64	NOTE	368
linux-release-x86_64	NOTE	534
macos-release-arm64	FAIL	96
macos-release-x86_64	FAIL	263
macos-oldrel-arm64	FAIL	71
macos-oldrel-x86_64	FAIL	293
windows-devel-arm64	NOTE	515
windows-devel-x86_64	NOTE	436
windows-release-arm64	NOTE	511
windows-release-x86_64	NOTE	433
windows-oldrel-x86_64	NOTE	471
wasm-release	FAIL	196

Exports:allocateCells corDensity findNbrsGrid findNbrsSNN findNbrsSpatial findROI getClusters getContour getHVG getNiche globalMoran gridDensity gridSPE localMoran mergeROI normalizeAssay plotCellCompo plotContour plotCorHeatmap plotDensCor plotDensity plotDots plotDR plotGrid plotImage plotLISA plotLISAscatter plotPCA plotROI plotSpatial plotUMAP plotViolin postSelRegion readProseg readVisium readVisiumHD readXenium realignVisium realignVisiumHD runPCA runUMAP selectRegion spe2PB

Dependencies:abind arrow askpass assertthat assorthead base64enc beachmat BH Biobase BiocFileCache BiocGenerics biocmake BiocNeighbors BiocParallel bit bit64 bitops blob bslib cachem class classInt cli codetools commonmark cpp11 crosstalk curl data.table DBI dbplyr dbscan DelayedArray DelayedMatrixStats deldir digest dir.expiry dplyr dqrng DropletUtils e1071 EBImage edgeR evaluate farver fastmap fastmatrix fftwtools filelock FNN fontawesome formatR fs futile.logger futile.options generics GenomicRanges ggplot2 glue goftest gtable h5mread HDF5Array hexbin hexDensity highr hms htmltools htmlwidgets httpuv httr httr2 igraph IRanges irlba isoband janitor jpeg jquerylib jsonlite KernSmooth knitr labeling lambda.r later lattice lazyeval lifecycle limma locfit lubridate lwgeom magick magrittr Matrix MatrixGenerics matrixStats memoise mime nlme openssl otel pheatmap pillar pkgconfig plotly png polyclip promises proxy purrr R.methodsS3 R.oo R.utils R6 rappdirs RBioFormats RColorBrewer Rcpp RcppAnnoy RcppEigen RcppProgress RCurl rhdf5 rhdf5filters Rhdf5lib rJava rjson rlang rmarkdown RSpectra RSQLite s2 S4Arrays S4Vectors S7 sass scales scuttle Seqinfo sf shiny SingleCellExperiment sitmo snakecase snow sourcetools SparseArray sparseMatrixStats SpatialExperiment SpatialPack spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.univar spatstat.utils statmod stringi stringr SummarizedExperiment sys tensor tibble tidyr tidyselect tiff timechange tinytex units utf8 uwot vctrs viridisLite withr wk xfun xtable XVector yaml

A quick start guide to the scider package

Rendered fromscider_userGuide.Rmdusingknitr::rmarkdown

Last update: 2025-10-03
Started: 2023-10-30

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Subset for grid level analysis	[,SpatialExperiment,ANY,ANY,ANY-method
Annotate all cells with contour level of cell type-specific density.	allocateCells
Check which cells are in which regions	cellsInRegion
Perform kernel density estimation on SpatialExperiment	computeDensity
Perform kernel density estimation on SpatialExperiment	computeDensityHex
Draw a contour region on some density level	contour2sf
Hash two 15-bytes signed integers into one 32-bytes integer.	coord_hash
Test for density correlation between two cell types.	corDensity
Construct a neighbour list from grid coordinates.	findNbrsGrid
Construct a SNN neighbour list from assay.	findNbrsSNN
Construct a distance-based neighbour list from cell coordinates.	findNbrsSpatial
Find ROIs based on cell type-specific densities via graph-based method.	findROI
Cluster cells in spe using graph methods.	getClusters
Get contour from density	getContour
Calculate areas between every two density levels	getContourRegions
Get top highly variable genes.	getHVG
Build a niche assay based on the profile of neighbouring cells	getNiche
Calculate global Moran for 1 to 2 variables.	globalMoran
Convert x,y nodes to data.frame of polygons	grid2df
Convert x,y nodes to sf polygons	grid2sf
Perform kernel density estimation on SpatialExperiment for cell types of interest	gridDensity
Summarize a SpatialExperiment object at grid-level	gridSPE
Calculate local Moran for 1 to 2 variables.	localMoran
Manually merge ROIs	mergeROI
Perform log normalization for counts	normalizeAssay
Plot cell type composition in each density level of cell of interest.	plotCellCompo
Plot contour lines.	plotContour
Visualising an sf object (for internal use only at the moment)	plotContourRegion
Plot model statistics using heatmap.	plotCorHeatmap
Plot density correlation between two cell types	plotDensCor
Plot grid-based density.	plotDensity
Dot plot of gene expression by groups	plotDots
Plot reduced dimensions.	plotDR plotPCA plotUMAP
Plot grid from metadata.	plotGrid
Plot background image of spe	plotImage
Plotting LISA (e.g. moran)	plotLISA
Scatterplot for local moran's I	plotLISAscatter
Plot ROIs on spatial.	plotROI
Plot cells based on spatial coordinates.	plotSpatial
Violin plot using genes or cell data	plotViolin
Merge sel_region from the selectRegion function to SpatialExperiment.	postSelRegion
Read Proseg V2 output into spe	readProseg
Read Visium output into spe	readVisium
Read VisiumHD output into spe	readVisiumHD
Read Xenium output into spe	readXenium
Scale and straighten out Visium coordinates	realignVisium
Scale and straighten out VisiumHD coordinates	realignVisiumHD
Fast PCA using irlba.	runPCA
UMAP using uwot. Parameters are set to be similar to Seurat's	runUMAP
Select region of interest from plot	selectRegion
Given a 'SpatialExperiment' data object, create pseudo-bulk samples using the colData information and return a DGEList object	spe2PB
Update the x,y limits of a plot	update_bound