srtsim_count_affine: Generate Data with Estimated Parameters For A New Designed...

In SRTsim: Simulator for Spatially Resolved Transcriptomics

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)

SRTsim documentation built on Jan. 13, 2023, 5:12 p.m.