View source: R/CorrelationScreen.R
calculate.rho.signed | R Documentation |
correlation analysis with FDR calculation
calculate.rho.signed(datExpr,n.perm = 10,FDR.cutoff = 0.05,estimator = "pearson",
use.obs = "na.or.complete",
direction = "absolute",
rho.thresh = NULL,sort.el = TRUE)
datExpr |
gene expression data matrix |
n.perm |
Number of permutations to perform. If |
FDR.cutoff |
FDR threshold to output final results of significant correlations. |
estimator |
Type of correlation coefficient to calculate, and gets passed to 'method' in 'cor()' function. Either "pearson" or "spearman". |
direction |
If direction = "absolute", absolute valued correlations are considered. If direction = "positive" or "negative", signed correlation is considered, and significance is calculated for positive/negative values. |
rho.thresh |
vector of correlation cutoff threshold to calculate significance. If NULL, threshold values will be generated by increment of 0.01 between -1 and 1 (if direction = "positive" or "negative"), or 0 and 1 (if direction = "absolute"). |
sort.el |
logical value to determine whether correlation list should be sorted |
use.obs |
an optional character string giving a method for computing covariances in the presence of missing values. This must be (an abbreviation of) one of the strings "everything", "all.obs", "complete.obs", "na.or.complete", or "pairwise.complete.obs". |
direction = "absolute" can serve as two-tailed significance test, where as direction = "positive"/"negative" is one-tailed test.
output is a list. output$signif.ijw is three column edgelist data.frame, third column being the weight. output$FDR is the permutation FDR table across the threshold values in rho.thresh.
Won-Min Song
data(Sample_Expression)
rho.out = calculate.rho.signed(datExpr,n.perm = 10,FDR.cutoff = 0.05,estimator = "pearson",
use.obs = "na.or.complete",
direction = "absolute",
rho.thresh = NULL,sort.el = TRUE)
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