tronco.capri {TRONCO} | R Documentation |
Reconstruct a progression model using CAPRI algorithm. For details and examples regarding the inference process and on the algorithm implemented in the package, we refer to the Vignette Section 6.
tronco.capri(data, command = "hc", regularization = c("bic", "aic"), do.boot = TRUE, nboot = 100, pvalue = 0.05, min.boot = 3, min.stat = TRUE, boot.seed = NULL, silent = FALSE, epos = 0, eneg = 0, restart = 100)
data |
A TRONCO compliant dataset. |
command |
Parameter to define to heuristic search to be performed. Hill Climbing and Tabu search are currently available. |
regularization |
Select the regularization for the likelihood estimation, e.g., BIC, AIC. |
do.boot |
A parameter to disable/enable the estimation of the error rates give the reconstructed model. |
nboot |
Number of bootstrap sampling (with rejection) to be performed when estimating the selective advantage scores. |
pvalue |
Pvalue to accept/reject the valid selective advantage relations. |
min.boot |
Minimum number of bootstrap sampling to be performed. |
min.stat |
A parameter to disable/enable the minimum number of bootstrap sampling required besides nboot if any sampling is rejected. |
boot.seed |
Initial seed for the bootstrap random sampling. |
silent |
A parameter to disable/enable verbose messages. |
epos |
Error rate of false positive errors. |
eneg |
Error rate of false negative errors. |
restart |
An integer, the number of random restarts. |
A TRONCO compliant object with reconstructed model
data(test_dataset) recon = tronco.capri(test_dataset, nboot = 1)