Introduction | Simple Usage
Package: SpaTopic 1.3.1.9000
SpaTopic: Topic Inference to Identify Tissue Architecture in Multiplexed Images
A novel spatial topic model to integrate both cell type and spatial information to identify the complex spatial tissue architecture on multiplexed tissue images without human intervention. The Package implements a collapsed Gibbs sampling algorithm for inference. The method is highly scalable to large-scale image datasets without extracting neighborhood information for every single cell. The package supports spatially resolved cell-level data analysis, topic inference, visualization, and downstream biological interpretation of tissue microenvironments.
Authors:
SpaTopic_1.3.1.9000.tar.gz
SpaTopic_1.3.1.9000.zip(r-4.7)SpaTopic_1.3.1.9000.zip(r-4.6)SpaTopic_1.3.1.9000.zip(r-4.5)
SpaTopic_1.3.1.9000.tgz(r-4.6-x86_64)SpaTopic_1.3.1.9000.tgz(r-4.6-arm64)SpaTopic_1.3.1.9000.tgz(r-4.5-x86_64)SpaTopic_1.3.1.9000.tgz(r-4.5-arm64)
SpaTopic_1.3.1.9000.tar.gz(r-4.7-arm64)SpaTopic_1.3.1.9000.tar.gz(r-4.7-x86_64)SpaTopic_1.3.1.9000.tar.gz(r-4.6-arm64)SpaTopic_1.3.1.9000.tar.gz(r-4.6-x86_64)
SpaTopic_1.3.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SpaTopic/json (API)
| # Install 'SpaTopic' in R: |
| install.packages('SpaTopic', repos = c('https://xiyupeng.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/xiyupeng/spatopic/issues
Pkgdown/docs site:https://xiyupeng.github.io
Uses libs:
Datasets:
- lung5 - Example input data for 'SpaTopic'
Last updated from:cf1dab7aad. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 159 | ||
| linux-devel-x86_64 | OK | 149 | ||
| source / vignettes | OK | 276 | ||
| linux-release-arm64 | OK | 153 | ||
| linux-release-x86_64 | OK | 157 | ||
| macos-release-arm64 | OK | 190 | ||
| macos-release-x86_64 | OK | 241 | ||
| macos-oldrel-arm64 | OK | 201 | ||
| macos-oldrel-x86_64 | OK | 324 | ||
| windows-devel | OK | 144 | ||
| windows-release | OK | 153 | ||
| windows-oldrel | OK | 151 | ||
| wasm-release | OK | 169 |
Exports:frex_topiclabel_topicslift_topicprob_topicscore_topicSeurat5obj_to_SpaTopicSpaTopic_inferencestratified_sampling_3D_via_2Dstratified_sampling_sf
Dependencies:classclassIntcodetoolsDBIe1071foreachiteratorsKernSmoothMASSproxyRANNRcppRcppArmadilloRcppProgresss2sfunitswk
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Calculate FREX ranked words and values for a topic | frex_topic |
| Label topics function | label_topics |
| Calculate lift ranked words and values for a topic | lift_topic |
| Example input data for 'SpaTopic' | lung5 |
| Print method for SpaTopic objects | print.SpaTopic |
| Calculate highest probability words and values for a topic | prob_topic |
| Calculate score ranked words and values for a topic | score_topic |
| Convert a Seurat v5 object as the input of 'SpaTopic' | Seurat5obj_to_SpaTopic |
| 'SpaTopic': fast topic inference to identify tissue architecture in multiplexed images | SpaTopic_inference |
| Format messages for SpaTopic package | spatopic_message |
| A class of the output from 'SpaTopic' | SpaTopic-class |
| SpaTopic: Spatial Topic Modeling for Multiplexed Images | SpaTopic-package SpaTopic SpaTopic-Package |
| Spatially stratified random sample points from a 3D image using 2D slicing. | stratified_sampling_3D_via_2D |
| Spatially stratified random sample points from an image. | stratified_sampling_sf |
