Package: CTSV 1.7.0

Jinge Yu Developer

CTSV: Identification of cell-type-specific spatially variable genes accounting for excess zeros

The R package CTSV implements the CTSV approach developed by Jinge Yu and Xiangyu Luo that detects cell-type-specific spatially variable genes accounting for excess zeros. CTSV directly models sparse raw count data through a zero-inflated negative binomial regression model, incorporates cell-type proportions, and performs hypothesis testing based on R package pscl. The package outputs p-values and q-values for genes in each cell type, and CTSV is scalable to datasets with tens of thousands of genes measured on hundreds of spots. CTSV can be installed in Windows, Linux, and Mac OS.

Authors:Jinge Yu Developer [aut, cre], Xiangyu Luo Developer [aut]

CTSV_1.7.0.tar.gz
CTSV_1.7.0.zip(r-4.5)CTSV_1.7.0.zip(r-4.4)CTSV_1.7.0.zip(r-4.3)
CTSV_1.7.0.tgz(r-4.4-any)CTSV_1.7.0.tgz(r-4.3-any)
CTSV_1.7.0.tar.gz(r-4.5-noble)CTSV_1.7.0.tar.gz(r-4.4-noble)
CTSV_1.7.0.tgz(r-4.4-emscripten)CTSV_1.7.0.tgz(r-4.3-emscripten)
CTSV.pdf |CTSV.html✨
CTSV/json (API)
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Bug tracker:https://github.com/jingeyu/ctsv/issues

On BioConductor:CTSV-1.7.0(bioc 3.20)CTSV-1.6.0(bioc 3.19)

bioconductor-package

2 exports 0.36 score 95 dependencies

Last updated 2 months agofrom:1a6e09e7cc

Exports:CTSVsvGene

Dependencies:abindaskpassBHBiobaseBiocFileCacheBiocGenericsBiocParallelbitbit64blobcachemclicodetoolscolorspacecpp11crayoncurlDBIdbplyrDelayedArraydplyrevaluatefansifarverfastmapfilelockformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehighrhttrIRangesisobandjsonliteknitrlabelinglambda.rlatticelifecyclemagickmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplogrplyrpsclpurrrqvalueR6RColorBrewerRcppreshape2rjsonrlangRSQLiteS4ArraysS4VectorsscalesSingleCellExperimentsnowSparseArraySpatialExperimentstringistringrSummarizedExperimentsystibbletidyrtidyselectUCSC.utilsutf8vctrsviridisLitewithrxfunXVectoryamlzlibbioc