###############################################################################
# DE summary
###############################################################################
RC_DESummary = function(res, FC, r_FC, padj, r_pval){
# We create an empty dataframe
df_sum = matrix(nrow = length(r_FC), ncol = length(r_pval), NA) %>% as.data.frame
# Row iteration initializing
ci = 0
for(i in r_FC){
ci = ci + 1
# Col iteration initialzing
cj = 1
for(j in r_pval){
# Find the number of DE features in Res with respect to the iterating values
nDE = nrow(res[ abs(res[,FC]) > i & res[,padj] < j, ])
# Save the value
df_sum[ci,cj] = nDE
cj = cj + 1
}
}
colnames(df_sum) = paste("Stat",r_pval,sep="_")
rownames(df_sum) = paste("Change",r_FC,sep="_")
# return the DF
return(df_sum)
}
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