rm(list = ls(all.names = TRUE))
set.seed(12345)
library("DGCA",lib="~/.Rlib")
options(stringsAsFactors = FALSE)
message("loading data")
message(Sys.time())
data(darmanis) #loads daramanis
data(design_mat) #loads design_mat
######################
split = 5 #number of times to split the input. This means split**2 comparisons will be run (see below)
nPerms = 15 #permutations to run
outputfile = "output.test.txt" #output file (TSV)
input_data = darmanis #input dataframe
design_mat = design_mat #input design matrix
groups = c("oligodendrocyte", "neuron") #groups to examine
num_cores = 2 #cores per worker
corrType="pearson" #correlation type (pearson, spearman, bicor, mutualinformation)
######################
ddcorAllParallel(input_data, design_mat, groups, outputfile,
sigOutput=TRUE,corrType=corrType,adjust="perm",
nPerms=nPerms,verbose=TRUE,perBatch=split,
coresPerJob=num_cores,batchDir="minimal",testJob=TRUE,
memPerJob = 10000,timePerJob=60)
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