RESUMO
Isobaric peptide termini labeling ( IPTL) is a technology which uses light and heavy isotopes to label C-terminus and N-terminus of peptides. As the masses of labeled peptides are equivalent, the complexity of sample is low when analyzing MS data produced by this technology. Besides, paired b and y ions are helpful while analyzing MS/MS data in this kind of experiments. On the basis of this, a novel scoring algorithm, all ions scoring algorithm (AISA), has been designed for IPTL experiments. The information of quantification and qualification can be acquired at the same time using AISA. On Q-Exactive HeLa 2D RPLC dataset, peptide spectrum matches ( PSMs) , distinct peptides and protein groups identified by AISA are 15%, 26%and 22% higher than Morpheus. On human-HCC-HL dataset, PSMs, distinct peptides and protein groups identified by AISA are 24%, 39% and 27% higher than Morpheus. Quantification ratio on Q-Exactive HeLa and human-HCC-HL datasets are 1. 18 and 0. 90, respectively, which are very close to 1. Besides, quantification ratios between 0. 5 and 2. 0 are 91% and 94%, respectively.
RESUMO
Isobaric peptide termini labeling ( IPTL) is a technology which uses light and heavy isotopes to label C-terminus and N-terminus of peptides. As the masses of labeled peptides are equivalent, the complexity of sample is low when analyzing MS data produced by this technology. Besides, paired b and y ions are helpful while analyzing MS/MS data in this kind of experiments. On the basis of this, a novel scoring algorithm, all ions scoring algorithm (AISA), has been designed for IPTL experiments. The information of quantification and qualification can be acquired at the same time using AISA. On Q-Exactive HeLa 2D RPLC dataset, peptide spectrum matches ( PSMs) , distinct peptides and protein groups identified by AISA are 15%, 26%and 22% higher than Morpheus. On human-HCC-HL dataset, PSMs, distinct peptides and protein groups identified by AISA are 24%, 39% and 27% higher than Morpheus. Quantification ratio on Q-Exactive HeLa and human-HCC-HL datasets are 1. 18 and 0. 90, respectively, which are very close to 1. Besides, quantification ratios between 0. 5 and 2. 0 are 91% and 94%, respectively.