Package: RegionalST 1.5.8

Ziyi Li

RegionalST: Investigating regions of interest and performing regional cell type-specific analysis with spatial transcriptomics data

This package analyze spatial transcriptomics data through cross-regional cell type-specific analysis. It selects regions of interest (ROIs) and identifys cross-regional cell type-specific differential signals. The ROIs can be selected using automatic algorithm or through manual selection. It facilitates manual selection of ROIs using a shiny application.

Authors:Ziyi Li [aut, cre]

RegionalST_1.5.8.tar.gz
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RegionalST.pdf |RegionalST.html✨
RegionalST/json (API)
NEWS

# Install 'RegionalST' in R:

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

Datasets:

exampleRes - Example DE output
example_sce - Example single cell experiment for input
pathways_hallmark - Hallmark database
pathways_kegg - KEGG database
pathways_reactome - REACTOME database

On BioConductor:RegionalST-1.5.8(bioc 3.21)RegionalST-1.4.2(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

spatial transcriptomics reactome kegg

4.30 score 8 scripts 130 downloads 16 exports 243 dependencies

Last updated 2 months agofrom:0ddee1b51e. Checks:1 OK, 6 NOTE. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Jan 05 2025
R-4.5-win	NOTE	Jan 05 2025
R-4.5-linux	NOTE	Jan 05 2025
R-4.4-win	NOTE	Jan 05 2025
R-4.4-mac	NOTE	Jan 05 2025
R-4.3-win	NOTE	Jan 05 2025
R-4.3-mac	NOTE	Jan 05 2025

Exports:DoGSEA DrawDotplot DrawRegionProportion DrawRegionProportion_withProp FindRegionalCells GetCellTypeSpecificDE_withProp GetCrossRegionalDE_raw GetCrossRegionalDE_withProp GetOneRadiusEntropy GetOneRadiusEntropy_withProp getProportion ManualSelectCenter mySpatialPreprocess PlotOneSelectedCenter RankCenterByEntropy RankCenterByEntropy_withProp

Dependencies:abind arrow askpass assertthat assorthead base64enc BayesSpace beachmat beeswarm BH Biobase BiocFileCache BiocGenerics BiocManager BiocNeighbors BiocParallel BiocSingular BiocStyle bit bit64 bitops blob bluster bookdown bslib cachem Cairo caTools class cli cluster coda codetools colorspace commonmark corpcor cowplot cpp11 crayon crosstalk curl data.table DBI dbplyr DelayedArray deldir digest DirichletReg doParallel dotCall64 dplyr dqrng e1071 edgeR EpiDISH evaluate fansi farver fastDummies fastmap fastmatch fgsea filelock fitdistrplus FNN fontawesome forcats foreach formatR Formula fs futile.logger futile.options future future.apply generics GenomeInfoDb GenomeInfoDbData GenomicRanges GGally ggbeeswarm ggplot2 ggrastr ggrepel ggridges ggstats globals glue goftest gplots gridExtra gtable gtools here highr hms htmltools htmlwidgets httpuv httr ica igraph IRanges irlba isoband iterators jquerylib jsonlite KernSmooth knitr labeling lambda.r later lattice lazyeval leiden lifecycle limma listenv lmtest locfdr locfit magrittr MASS Matrix MatrixGenerics matrixStats maxLik mclust memoise metapod mgcv microbenchmark mime miniUI miscTools munsell nlme nnls openssl parallelly patchwork pbapply pheatmap pillar pkgconfig plogr plotly plyr png polyclip prettyunits progress progressr promises proxy purrr quadprog R6 ragg RANN rappdirs RColorBrewer Rcpp RcppAnnoy RcppArmadillo RcppDist RcppEigen RcppHNSW RcppML RcppProgress RcppTOML RCurl reshape2 reticulate rhdf5 rhdf5filters Rhdf5lib rjson rlang rmarkdown ROCR rprojroot RSpectra RSQLite rsvd Rtsne S4Arrays S4Vectors sandwich sass ScaledMatrix scales scater scattermore scran sctransform scuttle Seurat SeuratObject shiny SingleCellExperiment sitmo snow sourcetools sp spam SparseArray spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.univar spatstat.utils statmod stringi stringr SummarizedExperiment survival sys systemfonts tensor textshaping tibble tidyr tidyselect tinytex TOAST UCSC.utils utf8 uwot vctrs vipor viridis viridisLite withr xfun xgboost xtable XVector yaml zoo

Understanding Intrasample Heterogeneity from ST data with RegionalST

Ziyi Li

Rendered fromRegionalST.Rmdusingknitr::rmarkdownon Jan 05 2025.

Last update: 2024-11-11
Started: 2023-05-02

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Perform GSEA analysis for cross-regional DE genes	DoGSEA
Draw dot plot for GSEA results of cross-regional DE genes	DrawDotplot
Draw regional cell type distribution with cell type annotation information	DrawRegionProportion
Draw regional cell type distribution with cellular proportion information	DrawRegionProportion_withProp
Example single cell experiment for input	example_sce
Example DE output	exampleRes
Identify regional cells given centers and radiuses	FindRegionalCells
Identify cross-regional cell type-specific differential analysis with proportion	GetCellTypeSpecificDE_withProp
Identify cross-regional differential analysis	GetCrossRegionalDE_raw
Identify cross-regional differential analysis with proportion	GetCrossRegionalDE_withProp
Computer the entropy for a fixed radius	GetOneRadiusEntropy
Computer the entropy for a fixed radius with cell type proportion	GetOneRadiusEntropy_withProp
Define an accessor method for Proportion_CARD	getProportion
Manually select top ROIs	ManualSelectCenter
Perform Preprocessing for spatial data (tailored from BayesSpace function)	mySpatialPreprocess
Hallmark database	pathways_hallmark
KEGG database	pathways_kegg
REACTOME database	pathways_reactome
Plot one selected ROI	PlotOneSelectedCenter
Automatically rank ROI centers based on entropy	RankCenterByEntropy
Automatically rank ROI centers based on entropy with proportions	RankCenterByEntropy_withProp