Note that pybind11 is required for installation. It can be installed via pip or conda.
pip install pybind11
conda install -c conda-forge pybind11
mkdir build
cd build
cmake ../ -DLIBLEMON_ROOT=/scratch/software/lemon/ -DBOOST_ROOT=/scratch/software/boost_1_74_0/
make install
The clonelib package will be installed to the site-packages directory of your Python environment.
./generatecnatrees -minTotalCN 1 > cnatrees.txt
./simulate -S cnatrees.txt -dot T.dot > T.txt
dot -Tpdf T.dot > T.pdf
T.txt contains a text representantation of the simulated clonal tree. This can be visualized using:
./visualizephylo T.txt | dot -Tpdf > T.pdf
To remove unsampled nodes, use -r in simulate:
./simulate -r -n 50 -S cnatrees.txt -dot T.dot > T.txt
dot -Tpdf T.dot > T.pdf
Simulate will generate the trees, proportions, and node information.
Usage:
./simulate [--help|-h|-help] -S str [-dirich_param num] [-dot str] [-f]
[-k int] [-kk int] [-l int] [-m int] [-minProp num] [-n int]
[-num_tries int] [-output_file_dir str] [-purity num] [-r]
[-restrictLoss] [-s int] [-threshold num] [-uniform]
Where:
--help|-h|-help
Print a short help message
-S str
Input CNA tree file
-dirich_param num
symmetric concentration parameter for Dirichlet distribution (default 2)
-dot str
Graphviz DOT output filename (default: '', no output)
-f
Whether to output files
-k int
Number of segments (default: 10)
-kk int
Number of truncal segments (default: 5)
-l int
Number of mutation clusters (default: 5)
-m int
Number of samples (default: 2)
-minProp num
Minimum desired clone proportion (default: 0.05)
-n int
Number of SNVs (default: 1000)
-num_tries int
The number of tries for sampling mutation rejection sampling (default 1000)
-output_file_dir str
The directory for where to write output files
-purity num
Expected purity (default: 0.8)
-r
Remove unsampled nodes
-restrictLoss
Whether to restrict copy number loss (default false)
-s int
Random number generator seed (default: 0)
-threshold num
Minimum threshold for SNV proportions (default: 0.05)
-uniform
use uniform distribution for mutation assignments
Example run:
./simulate -r -S /build/cnatrees.txt -purity .99 -minProp .05 -kk 2 -f -s 12 -l 7 -k 50 -n 5000 -m 1 -output_file_dir /build/output/intermediate
Generate single cells will generate single cell data for the simulation instance
Usage: ./generatesinglecells [-num_cells] [-read_depth] [-alpha_fp] [-out_dir] -in_dir [k] [-m] [-e] [-add] [-sub] Where: -num_cells The number of cells to simulate with the single cell generation (default: 1000) -read_depth The read_depth for the single cell generation (default: .05) -alpha_fp The sequencing error for single cell generation (default .001) -out_dir The output directory for single cell generation (default: results) -in_dir The input directory of files for single cell generation (mandatory) -k Number of segments (default: 10)) -m Number of samples (default: 2) -e The error rate for CNA data (default: 0) -add The proportion of copy number errors adding an allele (default .3 -sub The proportion of copy number errors subtracting an allele (default .3)
(Please note: total copy number neutral CNAs will have a probability of 1 - (add + sub) )
Example run: ./generatesinglecells -num_cells 500 -read_depth 0.05 -alpha_fp 0.001 -k 50 -m 1 -e .3 -add .35 -sub .25 -out_dir /Users/annahart/CLionProjects/clonesim3/build/output/testing -in_dir /Users/annahart/CLionProjects/clonesim3/build/output/intermediate
With the aid of pybind11, clonelib has a python interface to certain functionality within clonelib. This functionality currently includes:
- enumeration of CNA trees give a set of allele-specific copy number states
- enumeration of genotype trees given a CNA tree
For more details on installation and usage, see PYBIND_README.md.
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