sigtestp {c3net} | R Documentation |
sigtestp
takes the data set as input and computes the mutual information matrix in which the nonsignificant elements are eliminated by using a significance threshold only (no MTC) - see details.
sigtestp( data, alpha, itnum)
data |
Data set where rows are variables (e.g. genes) and columns are samples. |
alpha |
Statistical significance threshold |
itnum |
Number of iterations to resample data to get sampling distribution. |
The data set is resampled completely at each iteration and at the end the sampling distribution is obtained for using in significance test.
sigtestp
returns environment res that contains the obtained threshold value res$I0. For advanced users, who are able to write code in R, we provided the variables obtained in the function so that one might want to make further analysis without running the function again. Please see the source code for the additional return values of the environment res.
G. Altay, F. Emmert-Streib, "Inferring the conservative causal core of gene regulatory networks", BMC Systems Biology (2010) 4:132.
makemim
, copula
, c3
,c3
, sigtestMTC
data(expdata) data(truenet) alpha <- 0.001 itnum <- 2 res <- sigtestp( expdata, alpha, itnum) net <- c3(res$Inew) # regulatory network inferred (non zero elements stand for links of # the predicted network) scores <- checknet(net,truenet)