Awesome
SCIFIL
Single Cell Inference of FItness Landscape
We propose a computational method for in vivo inference of clonal selection and estimate of fitness landscapes of heterogeneous cancer cell populations from single cell sequencing data.
It takes single cell data, mutation tree and estimates finesses of all mutations.
Parameters
n
- number of haplotypesm
- number of mutation (not counting repeated mutation)gv_file
- path to file with mutation tree in GraphcViz formatnames_file
(optional) - name of file with mutation namesoutput
(optional) - path for output file. Default "out.txt"method
(optional) - method to use for fitness calculation(default "heuristic"):heuristic
to use heuristicbrute_force
to use brute force in finding order of mutation event in time for fitness estimation
nRep
(optional) - number of repeated mutation(if any) starting from 1theta
(optional) - value of theta (mean cancer cells mutation rate). Default is 0.01.
infSCITE trees
To obtain the trees from data folder we used infSCITE with following parameters:
./infSCITE -i dataHou18.csv -n 18 -m 58 -r 1 -l 500000 -fd 3.45e-3 -ad 1.46e-1 -s -e .2 -p 10000 -d -rec 3 -o output/dataHou18/dataHou18 -a
./infSCITE -i dataHou18.csv -n 18 -m 58 -r 1 -l 500000 -fd 3.45e-3 -ad 1.46e-1 -s -e .2 -p 10000 -d -o output/dataHou18/dataHou18 -a
With third (SESN2) repeated mutation and without it respectively.
Hot to run
In console type and change to actual parameters:
matlab -nodisplay -nodesktop -r "n=<number>;m=<number>;gv_file='<input_gv_tree>';output='<output_file>';method='<method_name>';nRep=<number>;theta=<number>;SCIFIL"
Example:
matlab -nodisplay -nodesktop -r "gv_file='data/dataHou18_map0_rep3.gv';names_file='data/dataHou18names.txt';nRep=3;n=58;m=18;SCIFIL"
matlab -nodisplay -nodesktop -r "gv_file='data/dataHou18_map0_noRep.gv';names_file='data/dataHou18names.txt';n=58;m=18;SCIFIL"
Execution result:
There will be two figures. First represent mutation tree, second fitness landscape.
Output file
Output contains only one line - calculated fitness of mutations in the same order as in names file or as their numbers in gv file (if names file is not specified). Repeated mutation's fitness will be the last one, first number is root(healthy tissue) fitness rate.
1.0000 1.0152 1.0404 1.0208 1.0793 1.0097 1.1066 1.0580 1.1933 1.0490 1.0270 1.1387 1.0682 1.0925 1.1493 1.0049 1.1274 1.0182 1.0334 1.2875