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BMC Bioinformatics. 2016 Jun 17;17(1):244. doi: 10.1186/s12859-016-1133-3.

PGA: an R/Bioconductor package for identification of novel peptides using a customized database derived from RNA-Seq.

Author information

BGI-Shenzhen, Shenzhen, 518083, China.
Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA.
BGI-Shenzhen, Shenzhen, 518083, China.
Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.



Peptide identification based upon mass spectrometry (MS) is generally achieved by comparison of the experimental mass spectra with the theoretically digested peptides derived from a reference protein database. Obviously, this strategy could not identify peptide and protein sequences that are absent from a reference database. A customized protein database on the basis of RNA-Seq data is thus proposed to assist with and improve the identification of novel peptides. Correspondingly, development of a comprehensive pipeline, which provides an end-to-end solution for novel peptide detection with the customized protein database, is necessary.


A pipeline with an R package, assigned as a PGA utility, was developed that enables automated treatment to the tandem mass spectrometry (MS/MS) data acquired from different MS platforms and construction of customized protein databases based on RNA-Seq data with or without a reference genome guide. Hence, PGA can identify novel peptides and generate an HTML-based report with a visualized interface. On the basis of a published dataset, PGA was employed to identify peptides, resulting in 636 novel peptides, including 510 single amino acid polymorphism (SAP) peptides, 2 INDEL peptides, 49 splice junction peptides, and 75 novel transcript-derived peptides. The software is freely available from , and the example reports are available at .


The pipeline of PGA, aimed at being platform-independent and easy-to-use, was successfully developed and shown to be capable of identifying novel peptides by searching the customized protein database derived from RNA-Seq data.


MS/MS; Peptide identification; Proteogenomics; Proteomics; RNA-Seq

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