Integrated Proteomic Pipeline Using Multiple Search Engines for a Proteogenomic Study with a Controlled Protein False Discovery Rate
| Autor: | Ji Yeong Park, Hyoung Joo Lee, Eun Sun Ji, John R. Yates, Young Mok Park, Hyun Kyoung Lee, Kyung Hoon Kwon, Kwang Hoe Kim, Gun Wook Park, Heeyoun Hwang, Jin Young Kim, Sung Kyu Robin Park, Jong Shin Yoo, Ju Yeon Lee, Young Ki Paik |
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| Rok vydání: | 2016 |
| Předmět: |
Proteomics
0301 basic medicine False discovery rate Biology computer.software_genre Hippocampus Biochemistry Mass Spectrometry 03 medical and health sciences Search engine Mascot Human proteome project Humans False Positive Reactions Databases Protein Proteogenomics 030102 biochemistry & molecular biology NeXtProt Proteomic Profiling Computational Biology General Chemistry Pipeline (software) Search Engine Alternative Splicing 030104 developmental biology Data mining computer |
| Zdroj: | Journal of Proteome Research. 15:4082-4090 |
| ISSN: | 1535-3907 1535-3893 |
| Popis: | In the Chromosome-Centric Human Proteome Project (C-HPP), false-positive identification by peptide spectrum matches (PSMs) after database searches is a major issue for proteogenomic studies using liquid-chromatography and mass-spectrometry-based large proteomic profiling. Here we developed a simple strategy for protein identification, with a controlled false discovery rate (FDR) at the protein level, using an integrated proteomic pipeline (IPP) that consists of four engrailed steps as follows. First, using three different search engines, SEQUEST, MASCOT, and MS-GF+, individual proteomic searches were performed against the neXtProt database. Second, the search results from the PSMs were combined using statistical evaluation tools including DTASelect and Percolator. Third, the peptide search scores were converted into E-scores normalized using an in-house program. Last, ProteinInferencer was used to filter the proteins containing two or more peptides with a controlled FDR of 1.0% at the protein level. Finally, we compared the performance of the IPP to a conventional proteomic pipeline (CPP) for protein identification using a controlled FDR of1% at the protein level. Using the IPP, a total of 5756 proteins (vs 4453 using the CPP) including 477 alternative splicing variants (vs 182 using the CPP) were identified from human hippocampal tissue. In addition, a total of 10 missing proteins (vs 7 using the CPP) were identified with two or more unique peptides, and their tryptic peptides were validated using MS/MS spectral pattern from a repository database or their corresponding synthetic peptides. This study shows that the IPP effectively improved the identification of proteins, including alternative splicing variants and missing proteins, in human hippocampal tissues for the C-HPP. All RAW files used in this study were deposited in ProteomeXchange (PXD000395). |
| Databáze: | OpenAIRE |
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