Figure 5.

Percolator's algorithm for normalizing the scores from different cross-validation sets. The algorithm takes two inputs: a set <a onClick="popup('http://www.biomedcentral.com/1471-2105/13/S16/S3/mathml/M2','MathML',630,470);return false;" target="_blank" href="http://www.biomedcentral.com/1471-2105/13/S16/S3/mathml/M2">View MathML</a> containing sets of PSMs, and a significance threshold α. Each PSM is represented as a tuple: a score and an accompanying boolean indicating whether this is a decoy PSM. The function qValue takes as input a set of scored PSMs and finds the minimal score that achieves the specified significance α, and MedianDecoy returns the median decoy score from the given set. The function returns a combined collection of normalized scores.

Granholm et al. BMC Bioinformatics 2012 13(Suppl 16):S3   doi:10.1186/1471-2105-13-S16-S3