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correlation analysis with FDR calculation
calculate.correlation(datExpr,doPerm = 100,doPar = FALSE,num.cores = 8,method = "pearson", FDR.cutoff = 0.05,n.increment = 100,is.signed = FALSE, output.permFDR = TRUE,output.corTable = TRUE,saveto = NULL)
gene expression data matrix
Number of permutations to perform. If doPerm = NULL, calculates BH FDR p-values instead of permutation based FDR.
doPerm = NULL
TRUE/FALSE logical variable to choose parallelization. Parallelization is utilized when BH FDR p-values are calculated for all pairs.
number of cores to use in parallelization.
correlation method to be passed to cor for method argument.
cor
method
FDR threshold to output final results of significant correlations.
When permutation is utilized, 0 <= |rho| <= 1 is broken down into n.increment to map each |rho| cutoff to respective FDR.
TRUE/FALSE to indicate using signed/unsigned correlation.
TRUE/FALSE to choose to output permutation indices and FDR table.
folder to output results.
output is three column edgelist data.frame, third column being the weight.
If doPar = TRUE, then num.cores are registered for PCP.
doPar = TRUE
# NOT RUN { # test simplest case of planar network (a 3-clique). data(Sample_Expression) calculate.correlation(datExpr[1:100,],doPerm = 5) # }
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