srtsim_count_affine {SRTsim} | R Documentation |
Generate Data with Estimated Parameters For A New Designed Pattern
Description
Generate Data with Estimated Parameters For A New Designed Pattern
Usage
srtsim_count_affine(
simsrt,
reflabel,
targetlabel,
breaktie = "random",
nn_func = c("mean", "median", "ransam"),
nn_num = 5,
local_sid = NULL,
numCores = 1
)
Arguments
simsrt |
A SRTsim object with estimated parameters from fitting step |
reflabel |
A character vector specifying labels for reference regions |
targetlabel |
A character vector specifying labels for target regions |
breaktie |
A character string specifying how ties are treated. Same as the "tie.method" in rank function |
nn_func |
A character string specifying how the psedo-count to be generated. options include 'mean','median' and 'ransam'. |
nn_num |
A integer of nearest neighbors, default is 5. |
local_sid |
A numberic seed used locally for the affine transformation. Default is NULL. |
numCores |
A number of cores to use |
Value
Returns a SRTsim object with a newly generated count matrix
Examples
## Prepare Data From LIBD Sample
subinfo <- exampleLIBD$info[,c("imagecol","imagerow","layer")]
colnames(subinfo) <- c("x","y","label")
gns <- c("ENSG00000168314","ENSG00000183036", "ENSG00000132639" )
## Create a simSRT Object with Three Genes For a Fast Example
simSRT1 <- createSRT(count_in= exampleLIBD$count[gns,],loc_in =subinfo)
## Estimate model parameters for data generation: domain-specific
simSRT1 <- srtsim_fit(simSRT1,sim_schem="domain")
## Define New Layer Structures
simSRT1@refcolData$target_label <- "NL1"
simSRT1@refcolData$target_label[simSRT1@refcolData$label %in% paste0("Layer",4:5)] <- "NL2"
simSRT1@refcolData$target_label[simSRT1@refcolData$label %in% c("Layer6","WM")] <- "NL3"
## Perform Data Generation for New Defined Layer Structures
## Reference: WM --> NL3, Layer5--> NL2, Layer3 --> NL1
simSRT1 <- srtsim_count_affine(simSRT1,
reflabel=c("Layer3","Layer5","WM"),
targetlabel=c("NL1","NL2","NL3"),
nn_func="ransam"
)
## Visualize the Expression Pattern for Gene of Interest
visualize_gene(simsrt=simSRT1,plotgn = "ENSG00000168314",rev_y=TRUE,ptsizeCount=1)
[Package SRTsim version 0.99.6 Index]