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TRONCO (version 2.4.2)

tronco.capri: tronco capri

Description

Reconstruct a progression model using CAPRI algorithm

Usage

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)

Arguments

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.

Value

A TRONCO compliant object with reconstructed model

Examples

Run this code
data(test_dataset)
recon = tronco.capri(test_dataset, nboot = 1)

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