python reimplementation of mProphet algorithm. For more information, see the following publication:
Reiter L, Rinner O, Picotti P, Hüttenhain R, Beck M, Brusniak MY, Hengartner MO, Aebersold R. mProphet: automated data processing and statistical validation for large-scale SRM experiments. Nat Methods. 2011 May;8(5):430-5. doi: 10.1038/nmeth.1584. Epub 2011 Mar 20.
In short, the algorithm can take targeted proteomics data, learn a linear separation between true signal and the noise signal and then compute a q-value (false discovery rate) to achieve experiment-wide cutoffs.
Install pyprophet from Python package index:
$ pip install numpy
$ pip install pyprophet
pyoprophet is not only a Python package, but also a command line tool:
$ pyprophet --help
or:
$ pyprophet --delim=tab tests/test_data.txt
The pyprophet tests are best executed using py.test and pytest-regtest plugin,
to run the tests use:
$ pip install pytest
$ pip install pytest-regtest
$ py.test tests