mProphet is a program that assigns a confidence of identification to multiple reaction monitoring (MRM) signals [1]. As a basis for that, mProphet uses the scores derived by mQuest and combines them in an optimal way using a semi-supervised learning approach. The resulting combined score exhibits a strong separation power and is used to keep only the high quality MRM data. In order to assign a confidence, mProphet utilizes negative controls (decoy transitions) which are in the measurement (see figure below). Decoy transitions quantify background noise resulting from the high complexity of analyzed protein samples and are used to statistically normalize the quality score.

1. Reiter L, Rinner O, Picotti P, Huttenhain R, Beck M, Brusniak MY, Hengartner MO, Aebersold R: mProphet: automated data processing and statistical validation for large-scale SRM experiments. Nature methods 2011, 8(5):430-435.