| runCORR |
runCORR |
| runCORR,SingleCellExperiment |
runCORR |
| runCORR,SVPExperiment |
runCORR |
| runCORR-method |
runCORR |
| runDetectMarker |
Detecting the specific cell features with nearest distance of cells in MCA space |
| runDetectMarker,SingleCellExperiment |
Detecting the specific cell features with nearest distance of cells in MCA space |
| runDetectMarker-method |
Detecting the specific cell features with nearest distance of cells in MCA space |
| runDetectSVG |
Detecting the spatially or single cell variable features with Moran's I or Geary's C |
| runDetectSVG,SingleCellExperiment |
Detecting the spatially or single cell variable features with Moran's I or Geary's C |
| runDetectSVG,SVPExperiment |
Detecting the spatially or single cell variable features with Moran's I or Geary's C |
| runDetectSVG-method |
Detecting the spatially or single cell variable features with Moran's I or Geary's C |
| runENCODE |
One hot encode for the specified cell category. |
| runENCODE,SingleCellExperiment |
One hot encode for the specified cell category. |
| runENCODE-method |
One hot encode for the specified cell category. |
| runGLOBALBV |
Global Bivariate analysis for spatial autocorrelation |
| runGLOBALBV,SingleCellExperiment |
Global Bivariate analysis for spatial autocorrelation |
| runGLOBALBV,SVPExperiment |
Global Bivariate analysis for spatial autocorrelation |
| runGLOBALBV-method |
Global Bivariate analysis for spatial autocorrelation |
| runKldSVG |
Detecting the spatially or single cell variable features with Kullback–Leibler divergence of 2D weighted kernel density estimation |
| runKldSVG,SingleCellExperiment |
Detecting the spatially or single cell variable features with Kullback–Leibler divergence of 2D weighted kernel density estimation |
| runKldSVG,SVPExperiment |
Detecting the spatially or single cell variable features with Kullback–Leibler divergence of 2D weighted kernel density estimation |
| runKldSVG-method |
Detecting the spatially or single cell variable features with Kullback–Leibler divergence of 2D weighted kernel density estimation |
| runLISA |
Local indicators of spatial association analysis |
| runLISA,SingleCellExperiment |
Local indicators of spatial association analysis |
| runLISA,SVPExperiment |
Local indicators of spatial association analysis |
| runLISA-method |
Local indicators of spatial association analysis |
| runLOCALBV |
Local Bivariate analysis with spatial autocorrelation |
| runLOCALBV,SingleCellExperiment |
Local Bivariate analysis with spatial autocorrelation |
| runLOCALBV,SVPExperiment |
Local Bivariate analysis with spatial autocorrelation |
| runLOCALBV-method |
Local Bivariate analysis with spatial autocorrelation |
| runMCA |
Run Multiple Correspondence Analysis |
| runMCA,SingleCellExperiment |
Run Multiple Correspondence Analysis |
| runMCA-method |
Run Multiple Correspondence Analysis |
| runSGSA |
Calculate the activity of gene sets in spatial or single-cell data with restart walk with restart and hyper test weighted. |
| runSGSA,SingleCellExperiment |
Calculate the activity of gene sets in spatial or single-cell data with restart walk with restart and hyper test weighted. |
| runSGSA-method |
Calculate the activity of gene sets in spatial or single-cell data with restart walk with restart and hyper test weighted. |
| runWKDE |
Calculating the 2D Weighted Kernel Density Estimation |
| runWKDE,SingleCellExperiment |
Calculating the 2D Weighted Kernel Density Estimation |
| runWKDE,SVPExperiment |
Calculating the 2D Weighted Kernel Density Estimation |
| runWKDE-method |
Calculating the 2D Weighted Kernel Density Estimation |
| sceSubPbmc |
a subset data of pbmck3 from SeuratData |
| SenMayoSymbol |
A gene set identifies senescent cells and predicts senescence-associated pathways across tissues |
| show-method |
Some accessor functions to get the internal slots of SVPExperiment |
| spatialCoords-method |
Some accessor functions to get the internal slots of SVPExperiment |
| spatialCoords<-,SVPExperiment |
Some accessor functions to get the internal slots of SVPExperiment |
| spatialCoords<--method |
Some accessor functions to get the internal slots of SVPExperiment |
| spatialCoordsNames-method |
Some accessor functions to get the internal slots of SVPExperiment |
| spatialCoordsNames<--method |
Some accessor functions to get the internal slots of SVPExperiment |
| svDf |
spatial or single cell variable features matrix extract method |
| svDf-method |
spatial or single cell variable features matrix extract method |
| svDf<- |
spatial or single cell variable features matrix extract method |
| svDf<--method |
spatial or single cell variable features matrix extract method |
| svDfNames |
spatial or single cell variable features matrix extract method |
| svDfNames-method |
spatial or single cell variable features matrix extract method |
| svDfNames<- |
spatial or single cell variable features matrix extract method |
| svDfNames<--method |
spatial or single cell variable features matrix extract method |
| svDfs |
spatial or single cell variable features matrix extract method |
| svDfs-method |
spatial or single cell variable features matrix extract method |
| svDfs<- |
spatial or single cell variable features matrix extract method |
| svDfs<--method |
spatial or single cell variable features matrix extract method |
| SVP-accessors |
Some accessor functions to get the internal slots of SVPExperiment |
| SVPExperiment |
The SVPExperiment class |
| SVPExperiment-class |
The SVPExperiment class |