Package: tpSVG 1.1.0
Boyi Guo
tpSVG: Thin plate models to detect spatially variable genes
The goal of `tpSVG` is to detect and visualize spatial variation in the gene expression for spatially resolved transcriptomics data analysis. Specifically, `tpSVG` introduces a family of count-based models, with generalizable parametric assumptions such as Poisson distribution or negative binomial distribution. In addition, comparing to currently available count-based model for spatially resolved data analysis, the `tpSVG` models improves computational time, and hence greatly improves the applicability of count-based models in SRT data analysis.
Authors:
tpSVG_1.1.0.tar.gz
tpSVG_1.1.0.zip(r-4.5)tpSVG_1.1.0.zip(r-4.4)tpSVG_1.1.0.zip(r-4.3)
tpSVG_1.1.0.tgz(r-4.4-any)tpSVG_1.1.0.tgz(r-4.3-any)
tpSVG_1.1.0.tar.gz(r-4.5-noble)tpSVG_1.1.0.tar.gz(r-4.4-noble)
tpSVG_1.1.0.tgz(r-4.4-emscripten)tpSVG_1.1.0.tgz(r-4.3-emscripten)
tpSVG.pdf |tpSVG.html✨
tpSVG/json (API)
NEWS
| # Install 'tpSVG' in R: |
| install.packages('tpSVG', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/boyiguo1/tpsvg/issues
On BioConductor:tpSVG-1.1.0(bioc 3.20)tpSVG-1.0.0(bioc 3.19)
Last updated 2 months agofrom:f0cabc5224
Exports:tpSVG
Dependencies:abindaskpassBHBiobaseBiocFileCacheBiocGenericsBiocParallelbitbit64blobcachemclicodetoolscpp11crayoncurlDBIdbplyrDelayedArraydplyrfansifastmapfilelockformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesgluehttrIRangesjsonlitelambda.rlatticelifecyclemagickmagrittrMatrixMatrixGenericsmatrixStatsmemoisemgcvmimenlmeopensslpillarpkgconfigplogrpurrrR6RcpprjsonrlangRSQLiteS4ArraysS4VectorsSingleCellExperimentsnowSparseArraySpatialExperimentstringistringrSummarizedExperimentsystibbletidyrtidyselectUCSC.utilsutf8vctrswithrXVectorzlibbioc
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Thin Plate Spline Model to Detect Spatially Variable Genes | tpSVG |
