crux percolator [options] <peptide-spectrum matches>


Percolator is a semi-supervised learning algorithm that dynamically learns to separate target from decoy peptide-spectrum matches (PSMs). The algorithm is described in this article:

Lukas Käll, Jesse Canterbury, Jason Weston, William Stafford Noble and Michael J. MacCoss. "Semi-supervised learning for peptide identification from shotgun proteomics datasets." Nature Methods. 4(11):923-925, 2007.

Percolator requires as input two collections of PSMs, one set derived from matching observed spectra against real ("target") peptides, and a second derived from matching the same spectra against "decoy" peptides. The output consists of ranked lists of PSMs, peptides and proteins. Peptides and proteins are assigned two types of statistical confidence estimates: q-values and posterior error probabilities.

The features used by Percolator to represent each PSM are summarized here.

Percolator also includes code from Fido, whch performs protein-level inference. The Fido algorithm is described in this article:

Oliver Serang, Michael J. MacCoss and William Stafford Noble. "Efficient marginalization to compute protein posterior probabilities from shotgun mass spectrometry data." Journal of Proteome Research. 9(10):5346-5357, 2010.

Crux includes code from Percolator. Crux Percolator differs from the stand-alone version of Percolator in the following respects:



The program writes files to the folder crux-output by default. The name of the output folder can be set by the user using the --output-dir option. The following files will be created: