Package: SpaNorm 1.5.2
SpaNorm: Spatially-aware normalisation for spatial transcriptomics data
This package implements the spatially aware library size normalisation algorithm, SpaNorm. SpaNorm normalises out library size effects while retaining biology through the modelling of smooth functions for each effect. Normalisation is performed in a gene- and cell-/spot- specific manner, yielding library size adjusted data.
Authors:
SpaNorm_1.5.2.tar.gz
SpaNorm_1.5.2.zip(r-4.6)SpaNorm_1.5.2.zip(r-4.5)
SpaNorm_1.5.2.tgz(r-4.6-any)SpaNorm_1.5.2.tgz(r-4.5-any)
SpaNorm_1.5.2.tar.gz(r-4.6-any)SpaNorm_1.5.2.tar.gz(r-4.5-any)
SpaNorm_1.5.2.tgz(r-4.5-emscripten)
SpaNorm.pdf |SpaNorm.html✨
SpaNorm/json (API)
NEWS
| # Install 'SpaNorm' in R: |
| install.packages('SpaNorm', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bhuvad/spanorm/issues
Pkgdown/docs site:https://bhuvad.github.io
- HumanDLPFC - Human dorsolateral prefrontal cortex (DLPFC) visium sample
On BioConductor:SpaNorm-1.5.2(bioc 3.23)SpaNorm-1.4.0(bioc 3.22)
softwaregeneexpressiontranscriptomicsspatialcellbiology
Last updated from:81ee46f8be. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | NOTE | 214 | ||
| linux-devel-x86_64 | NOTE | 623 | ||
| source / vignettes | OK | 594 | ||
| linux-release-x86_64 | NOTE | 625 | ||
| macos-devel-arm64 | NOTE | 421 | ||
| macos-release-arm64 | NOTE | 474 | ||
| windows-devel | NOTE | 952 | ||
| windows-release | NOTE | 927 | ||
| wasm-release | OK | 181 |
Exports:fastSizeFactorsfilterGenesplotCovariateplotSpatialSpaNormSpaNormPCASpaNormSVGtopSVGs
Dependencies:abindaskpassassortheadbeachmatBHBiobaseBiocFileCacheBiocGenericsBiocNeighborsBiocParallelBiocSingularbitbit64blobblustercachemcliclustercodetoolscpp11curlDBIdbplyrDelayedArraydigestdotCall64dplyrdqrngedgeRfarverfastmapfilelockformatRfutile.loggerfutile.optionsfuturefuture.applygenericsGenomicRangesggplot2globalsgluegtablehttr2igraphIRangesirlbaisobandlabelinglambda.rlatticelifecyclelimmalistenvlocfitmagickmagrittrMatrixMatrixGenericsmatrixStatsmemoisemetapodopensslparallellypillarpkgconfigprogressrpurrrR6rappdirsRColorBrewerRcppRcppEigenrjsonrlangRSQLitersvdS4ArraysS4VectorsS7ScaledMatrixscalesscranscuttleSeqinfoSeuratObjectSingleCellExperimentsitmosnowspspamSparseArraySpatialExperimentstatmodstringistringrSummarizedExperimentsystibbletidyrtidyselectutf8vctrsviridisLitewithrXVector
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Filter genes based on expression | fastSizeFactors fastSizeFactors,SpatialExperiment-method |
| Filter genes based on expression | filterGenes filterGenes,Seurat-method filterGenes,SpatialExperiment-method |
| Human dorsolateral prefrontal cortex (DLPFC) visium sample | HumanDLPFC |
| Diagnostic plot of predicted expression for a covariate | plotCovariate |
| Plot spatial transcriptomic annotations per spot | plotSpatial |
| Spatially-dependent normalisation for spatial transcriptomics data | SpaNorm SpaNorm,Seurat-method SpaNorm,SpatialExperiment-method |
| An S4 class to store a SpaNorm model fit | $,SpaNormFit-method SpaNormFit SpaNormFit-class |
| GLM-based (SpaNorm) PCA | SpaNormPCA SpaNormPCA,SpatialExperiment-method |
| Model-based spatially variable gene (SVG) calling | SpaNormSVG SpaNormSVG,SpatialExperiment-method |
| Export top SVG results to a data frame | topSVGs |
