condorCoreEnrich | R Documentation |
Compute one-sided KS and wilcox tests to determine if a subset of nodes has a stochastically larger qscore distribution.
condorCoreEnrich(test_nodes, q, perm = FALSE, plot.hist = FALSE, nsamp = 1000)
test_nodes |
is a list containing the subset of nodes (of one node class –blue or red–only) to be tested |
q |
is a two column data frame containing the node names in the first column and the q-scores in the second column. |
perm |
if TRUE, run permutation tests. Else, run
|
plot.hist |
if TRUE, produces two histograms of test statistics from permutation tests, one for KS and one for wilcoxon and a red dot for true labeling. Only works if perm=TRUE. |
nsamp |
Number of permutation tests to run |
if perm=FALSE
, the analytical p-values from
ks.test
and wilcox.test
if perm=TRUE
, the permutation p-values are provided in
addition to the analytical values.
ks.test
and wilcox.test
will throw warnings due to the presence of ties, so the p-values will be
approximate. See those functions for further details.
r = c(1,1,1,2,2,2,3,3,3,4,4);
b = c(1,2,3,1,2,4,2,3,4,3,4);
reds <- c("Alice","Sue","Janine","Mary")
blues <- c("Bob","John","Ed","Hank")
elist <- data.frame(red=reds[r],blue=blues[b])
condor.object <- createCondorObject(elist)
condor.object <- condorCluster(condor.object)
condor.object <- condorQscore(condor.object)
q_in <- condor.object$qscores$red.qscore
out <- condorCoreEnrich(c("Alice","Mary"),q=q_in,perm=TRUE,plot.hist=TRUE)
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