• Validate protein identifications using False Discovery Rates
• FDR support via concatenated or separate target and decoy databases
• Use Probability based measurements to verify protein assignments
• Use sensitivity and error plots to maintain an acceptable error rate
• Customize and filter data according to your needs
False Discovery Rates:
• Estimate global error rates with false discovery rate calculations at the protein and peptide level
• Use either separate or merged target and decoy databases
• Limit the frequency of random assignments
• Generate plots based on Mascot or SEQUEST scores, discriminate scores or probabilities
Probability:
• Model distribitions of correct versus incorrect assignments
• Assess reliability using a visual representation
• Save results as images or as text
Assess Sensitivity and Error:
• Create an effective balance between sensitivity and allowable error
• Maximize the number of protein identifications by choosing how to filter data
• Maintain an acceptable error rate
Comprehensive Data Reporting:
• Display all scores and metrics associated with every peptide and protein assignment
• Track how protein sets are filtered
• Customize results views to fit your needs
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