Combinatorial optimization method for identification of conserved evolutionary trajectories in tumors
- make (version 3.81 or higher)
- g++ (GCC version 4.1.2 or higher)
- Gurobi Optimizer
In the Makefile, set GUROBIROOT to the path of your root Gurobi folder.
Simply run make command in the root CONETT folder. It will create the executables.
Usage:
./conett -p [input tumor graph] -g [gene sets to be used as seeds] -t [minimum seed recurrence] -e [subgraph tumor conservation rate] -i [permutation p-value iterations] -a [edge weight cutoff] -f [outputFolder]| Parameters | Description |
|---|---|
-p |
Tumor graph file which shows temporal order of alterations |
-g |
(optional) File of gene (sets) that should be used as seeds |
-t |
Minimum recurrence frequency of the seeds |
-e |
Minimum number of tumors that each node on the trajectory has to follow the seed in |
-i |
(optional) The number of iterations for experimental estimation of the p-value of the size of the largest subgraph |
-a |
Threshold for the edge confidence in the ILP formulation |
-f |
Output folder name; all output files are placed into this folder |
Command to run:
./conett -p data/TRACERxDAGs_inac_singleRoot.txt -g SeedPathways.txt -t 10 -e 10 -f TRACERx_ccRCC_20191030 -a 0.85Tumor graph file is a transitive precedence graph, describing each directed edge with the name of the patient/sample and two pairs of node names and the corresponding alteration types. For example:
T001 GL - gene1 SNV
T001 GL - gene2 CNGAIN
T001 gene1 SNV gene2 CNGAIN
T002 GL - gene1 CNLOSS
...