Accessor function to retrieve the observed correlation from an 'cor_mg_result' object.
Value
A matrix contains the observation statistic for every gene and every cluster. Each row refers to a gene, and each column refers to a cluster
Examples
library(SpatialExperiment)
library(BumpyMatrix)
set.seed(100)
# simulate coordinates for clusters
df_clA <- data.frame(x = rnorm(n=10, mean=20, sd=5),
y = rnorm(n=10, mean=20, sd=5), cluster="A")
df_clB <- data.frame(x = rnorm(n=10, mean=100, sd=5),
y = rnorm(n=10, mean=100, sd=5), cluster="B")
clusters <- rbind(df_clA, df_clB)
clusters$sample="sample1"
# simulate coordinates for genes
trans_info <- data.frame(rbind(cbind(x = rnorm(n=10, mean=20, sd=5),
y = rnorm(n=10, mean=20, sd=5),
feature_name="gene_A1"),
cbind(x = rnorm(n=10, mean=20, sd=5),
y = rnorm(n=10, mean=20, sd=5),
feature_name="gene_A2"),
cbind(x = rnorm(n=10, mean=100, sd=5),
y = rnorm(n=10, mean=100, sd=5),
feature_name="gene_B1"),
cbind(x = rnorm(n=10, mean=100, sd=5),
y = rnorm(n=10, mean=100, sd=5),
feature_name="gene_B2")))
trans_info$x<-as.numeric(trans_info$x)
trans_info$y<-as.numeric(trans_info$y)
trans_info$cell = rep(paste("cell",1:20, sep=""), times=2)
mol <- BumpyMatrix::splitAsBumpyMatrix(
trans_info[, c("x", "y")],
row = trans_info$feature_name, col = trans_info$cell )
spe_sample1 <- SpatialExperiment(
assays = list(molecules = mol),sample_id ="sample1" )
w_x <- c(min(floor(min(trans_info$x)),
floor(min(clusters$x))),
max(ceiling(max(trans_info$x)),
ceiling(max(clusters$x))))
w_y <- c(min(floor(min(trans_info$y)),
floor(min(clusters$y))),
max(ceiling(max(trans_info$y)),
ceiling(max(clusters$y))))
set.seed(100)
corr_res <- compute_permp(x=spe_sample1,
cluster_info=clusters,
perm.size=10,
bin_type="square",
bin_param=c(2,2),
test_genes=unique(trans_info$feature_name),
correlation_method = "pearson",
n_cores=1,
correction_method="BH",
w_x=w_x ,
w_y=w_y)
#> Correlation Method = pearson
#> Running 10 permutation in sequential
# observed correlation
obs_corr <- get_cor(corr_res)