Improvement of peptide identification with considering the abundance of mRNA and peptide

Ma, Chunwei; Xu, Shaohang; Liu, Geng; Liu, Xin; Xu, Xun; Wen, Bo; Liu, Siqi

doi:10.1186/s12859-017-1491-5

BMC Bioinformatics

Table 1 Summary of peptide identification with 1% FDR in peptide level for different methods on two data sets

From: Improvement of peptide identification with considering the abundance of mRNA and peptide

No.	Methods	Jurkat cell line		Mouse liver
No.	Methods	Peptide	Improvement	Peptide	Improvement
1	DB_ref	71645	-	49937	-
2	DB_ref + DB_novel	71499	-	50083	-
3	DB_ref + DB_novel + R_low	72283	1.10%	50993	1.82%
4	DB_ref + DB_novel + R_low + F_mRNA	75649	5.80%	52503	4.83%
5	DB_ref + DB_novel + R_low + F_peptide	76259	6.66%	52170	4.17%
6	DB_ref + DB_novel + R_low + F_peptide+mRNA	77682	8.65%	53024	5.87%

Note:
1. DB_ref : searching MS/MS data against with the reference protein database and then using MascotPercolator to process the identification results
2. DB_ref + DB_novel : searching MS/MS data against with the reference protein database adding the novel transcript-derived proteins, and then using MascotPercolator to process the identification results
3. DB_ref + DB_novel + R_low : searching MS/MS data against with the customized protein database (reference proteins + novel transcript-derived proteins + removing low-RNA-level protein entries), and then using MascotPercolator to process the identification results
4. DB_ref + DB_novel + R_low + F_mRNA : searching MS/MS data against with the customized protein database (reference proteins + novel transcript-derived proteins + removing low-RNA-level protein entries), and then using MascotPercolator to process the identification results with adding the transcript abundance as a feature (F_mRNA)
5. DB_ref + DB_novel + R_low + F_peptide: searching MS/MS data against with the customized protein database (reference proteins + novel transcript-derived proteins + removing low-RNA-level protein entries), and then using MascotPercolator to process the identification results with adding the peptide abundance (MS1 XIC of peptide) as a feature (F_peptide)
6. DB_ref + DB_novel + R_low + F_peptide+mRNA: searching MS/MS data against with the customized protein database (reference proteins + novel transcript-derived proteins + removing low-RNA-level protein entries), and then using MascotPercolator to process the identification results with adding the two features (F_peptide+mRNA = F_mRNA + F_peptide)

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ISSN: 1471-2105

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