gpps: An ILP-based approach for inferring cancer progression with mutation losses from single cell data

ILP step

We provide gpps, that can be used to infer cancer progressions from single cell data. Differently from the previous tool, gpps employs a maximum likelihood search to find the best tree that explain the input, starting from single cell data.

The tool can be run with the following arguments:

  -m {perfect,persistent,dollo}, --model {perfect,persistent,dollo}
  -f FILE, --file FILE  path of the input file.
  -k K                  k-value of the selected model. Eg: Dollo(k)
  -t TIME, --time TIME  maximum time allowed for the computation. Type 0 to
                        not impose a limit.
  -o OUTDIR, --outdir OUTDIR
                        output directory.
  -e, --exp             set -e to get experimental-format results.
  -b FALSEPOSITIVE, --falsepositive FALSEPOSITIVE
                        set -b False positive probability.
  -a FALSENEGATIVE, --falsenegative FALSENEGATIVE
                        set -a False negative probability.

Where -a and -b are respectively the false negative and false positive rates for the Single Cell Sequencing.

Hill Climbing step

sage: hill_climbing.py [-h] -i ILPFILE -s SCSFILE -k K -o OUTDIR -b
                        FALSEPOSITIVE -a FALSENEGATIVE --ns NS --mi MI
                        [--names NAMES]

gpps- hill climber

optional arguments:
  -h, --help            show this help message and exit
  -i ILPFILE, --ilpfile ILPFILE
                        path of the ILP output file.
  -s SCSFILE, --scsfile SCSFILE
                        path of the SCS input file. (same input feeded to the
                        ILP)
  -k K                  k-value of the selected model. Eg: Dollo(k)
  -o OUTDIR, --outdir OUTDIR
                        output directory.
  -b FALSEPOSITIVE, --falsepositive FALSEPOSITIVE
                        set -b False positive probability.
  -a FALSENEGATIVE, --falsenegative FALSENEGATIVE
                        set -a False negative probability.
  --ns NS               Hill climbing neighbourhood size.
  --mi MI               Hill climbing maximum iterations.
  --names NAMES         Mutation names.