ETD CHARGE PREDICTION MACHINE

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Electron transfer dissociation (ETD) can dissociate highly charged ions. Efficient analysis of ions dissociated with ETD requires accurate determination of charge states for calculation of molecular weight. We created an algorithm to assign the charge state of ions often used for ETD. The program, Charge Prediction Machine (CPM), uses Bayesian decision theory to account for different charge reduction processes encountered in ETD and can also handle multiplex spectra. CPM correctly assigned charge states to 98% of the 13 097 MS2 spectra from a combined data set of four experiments. In a comparison between CPM and a competing program, Charger (ThermoFisher), CPM produced half the mistakes.