Journal
JOURNAL OF PROTEOME RESEARCH
Volume 15, Issue 12, Pages 4686-4695Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.6b00765
Keywords
proteogenomics; bioinformatics; workflow; mass spectrometry; genome annotation; testis
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Funding
- Wellcome Trust [WT098051]
- National Institutes of Health [U41HG007234]
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Proteogenomics leverages information derived from proteomic data to improve genome annotations. Of particular interest are novel peptides that provide direct evidence of protein expression for genomic regions not previously annotated as protein-coding. We present a modular, automated data analysis pipeline aimed at detecting such novel peptides in proteomic data sets. This pipeline implements criteria developed by proteomics and genome annotation experts for high-stringency peptide identification and filtering. Our pipeline is based on the OpenMS computational framework; it incorporates multiple database search engines for peptide identification and applies a machine-learning approach (Percolator) to post-process search results. We describe several new and improved software tools that we developed to facilitate proteogenomic analyses that enhance the wealth of tools provided by OpenMS. We demonstrate the application of our pipeline to a human testis tissue data set previously acquired for the Chromosome-Centric Human Proteome Project, which led to the addition of five new gene annotations on the human reference genome.
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