Objective To estimate the effect of two simple filters, two or more positive peptide filter and Unified Score filter on the true positive rate of protein and peptide. Methods Twenty-two LC-MS/MS datasets were from 18 ...Objective To estimate the effect of two simple filters, two or more positive peptide filter and Unified Score filter on the true positive rate of protein and peptide. Methods Twenty-two LC-MS/MS datasets were from 18 known protein mixture. Two or more positive peptide filter and Unified Score filter were applied to the 22 datasets. The filters effect was evaluated according to the true positive rate of protein and peptide for each filter. Results The positive rates of protein and peptide from two or more peptide filter raised from 56.49% to 92.86%-99.12% (for protein) and from 90.67% to 97.74%-99.62% (for peptide), but many positive proteins were filtered out. The positive rates of protein and peptide from Unified Score (ThermoFinnigan value 2400) were only about 35.51% and 82.99%, but after adjusted the value (3900) according to the number of false positive peptide, those positive rate raised to 63.61% (for protein) and 91.97% (for peptide). Conclusions Two or more peptides requirement could significantly decrease false positive rate, but it also may filter out many true positive proteins especially low molecular weight and less abundant proteins. Unified Score may be a better filter than Xcorr and DeltaCn combination and the value of 3900 is found to be more suitable for this particular datasets.展开更多
基金Supported by grants from the National Basic Research Program (973)2004CB520804 ,National Natural Science Foundation of China (30270657,30230150 ,3037030 ).
文摘Objective To estimate the effect of two simple filters, two or more positive peptide filter and Unified Score filter on the true positive rate of protein and peptide. Methods Twenty-two LC-MS/MS datasets were from 18 known protein mixture. Two or more positive peptide filter and Unified Score filter were applied to the 22 datasets. The filters effect was evaluated according to the true positive rate of protein and peptide for each filter. Results The positive rates of protein and peptide from two or more peptide filter raised from 56.49% to 92.86%-99.12% (for protein) and from 90.67% to 97.74%-99.62% (for peptide), but many positive proteins were filtered out. The positive rates of protein and peptide from Unified Score (ThermoFinnigan value 2400) were only about 35.51% and 82.99%, but after adjusted the value (3900) according to the number of false positive peptide, those positive rate raised to 63.61% (for protein) and 91.97% (for peptide). Conclusions Two or more peptides requirement could significantly decrease false positive rate, but it also may filter out many true positive proteins especially low molecular weight and less abundant proteins. Unified Score may be a better filter than Xcorr and DeltaCn combination and the value of 3900 is found to be more suitable for this particular datasets.
