In lulizou/spASE: Detecting Allele-Specific Expression in Spatial Transcriptomics

Example of running spASE on some simulated data.

library(spASE)

# Null simulation parameters
ngenes <- 100
numi <- 5
p <- 0.5
phi <- 0.2
a <- p*(1-phi)/phi
b <- (1-phi)*(1-p)/phi

# Simulate raw ASE data in a square
coords <- expand.grid(seq(1,5,0.1), seq(1,5,0.1))
npixels <- nrow(coords)

matrix1 <- matrix(nrow = ngenes, ncol = npixels)
matrix2 <- matrix(nrow = ngenes, ncol = npixels)

for (i in 1:ngenes) {
  lambda.p <- rbeta(npixels, a, b)
  matrix1[i,] <- rbinom(npixels, size=numi, prob=lambda.p)
  matrix2[i,] <- numi - matrix1[i,]
}

rownames(matrix1) <- rownames(matrix2) <- paste0('gene', seq(1,ngenes))
colnames(matrix1) <- colnames(matrix2) <- paste0('pixel', seq(1,npixels))

covariates <- cbind(data.frame(pixel = paste0('pixel',seq(1,npixels))),
                    coords)

results <- spase(matrix1, matrix2, covariates, cores=1)

# view the results data frame
results$result %>% arrange(qval)

# plot the results for the first gene
plotSpase(matrix1, matrix2, covariates, results, genes = 'gene28', coords=coords)

lulizou/spASE documentation built on May 22, 2024, 5:24 a.m.