-n: number of leaves-m: number of mutations-t: random seed for tree generation-s: random seed for mutation placement-o: output_prefix
- output_prefix_tree.dot: dot format tree with mutations as edge labels
- output_prefix_matrix.dot: mutation matrix of size
(2n-1) * m, where n is number of leaves and m is number of mutations.
python src/generate_perfect.py -n 3 -m 10 -t 90 -s 90 -o "perfect"
This will create two files named perfect_tree.dot and perfect_matrix.dot.
The first two arguments are for the perfect phylogeny cell (or clone) * mutation matrix and the perfect phylogeny in dot format. The remaining arguments are the following -
-k: K for K-Dollo loss.--loss: loss probability--mut-base: 0/1 (whether mutations are 0 or 1 indexed)-A: K-dollo helper matrix file in tsv format (K-dollo completion of B)-B: K-dollo mutation matrix file in tsv format (this is the input for reconstructing K-Dollo phylogenies)--dot: K-Dollo output tree in dot format
- output.A: K-dollo helper matrix (K-dollo completion of B)
- output.B: K-dollo mutation matrix (this is the input for reconstructing K-Dollo phylogenies)
- output.dot: K-Dollo output tree in dot format
python src/generate_dollo_from_perfect.py perfect_matrix.tsv perfect_tree.dot -k 1 --loss 0.1 -s 90 --mut-base 0 -A onedollo.A -B onedollo.B --dot onedollo_tree.dot
We generate coalescent trees using CellCoal. The command for running the program we use is -
./cellcoal-1.2.0 -n10 \
-s"num_leaves" \
-l10000 \
-e100000 \
-g1.0e-05 \
-j3000 \
-k1 \
-i1 \
-b0 \
-c0 \
-C5 \
-u1.0e-07 \
-f0.3 0.2 0.2 0.3 \
-r0.00 0.03 0.12 0.04 0.11 0.00 0.02 0.68 0.68 0.02 0.00 0.11 0.04 0.12 0.03 0.00 \
-1 -2 -3 -4 -6 -v -x -W \
-o"output_directory" \
-#200011
Description of the parameters:
-n: number of replicates-l: total sites in the genome-e: population size-g: exponential growth rate-j: number of sampled site-k: root branch length ratioi: rate variation among branchesb: alphabet (0 for binary)c: germline mutation rateC: sequencing coverageu: mutation rate per site per generationf: base frequenciesr: mutation matrix ACGT x ACGT -1 -2 -3 -4 -6 -v -x -W \o: output_directory \#: random seed