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The bacterial proteogenomic pipeline

BACKGROUND: Proteogenomics combines the cutting-edge methods from genomics and proteomics. While it has become cheap to sequence whole genomes, the correct annotation of protein coding regions in the genome is still tedious and error prone. Mass spectrometry on the other hand relies on good characte...

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Autores principales: Uszkoreit, Julian, Plohnke, Nicole, Rexroth, Sascha, Marcus, Katrin, Eisenacher, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4290607/
https://www.ncbi.nlm.nih.gov/pubmed/25521444
http://dx.doi.org/10.1186/1471-2164-15-S9-S19
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author Uszkoreit, Julian
Plohnke, Nicole
Rexroth, Sascha
Marcus, Katrin
Eisenacher, Martin
author_facet Uszkoreit, Julian
Plohnke, Nicole
Rexroth, Sascha
Marcus, Katrin
Eisenacher, Martin
author_sort Uszkoreit, Julian
collection PubMed
description BACKGROUND: Proteogenomics combines the cutting-edge methods from genomics and proteomics. While it has become cheap to sequence whole genomes, the correct annotation of protein coding regions in the genome is still tedious and error prone. Mass spectrometry on the other hand relies on good characterizations of proteins derived from the genome, but can also be used to help improving the annotation of genomes or find species specific peptides. Additionally, proteomics is widely used to find evidence for differential expression of proteins under different conditions, e.g. growth conditions for bacteria. The concept of proteogenomics is not altogether new, in-house scripts are used by different labs and some special tools for eukaryotic and human analyses are available. RESULTS: The Bacterial Proteogenomic Pipeline, which is completely written in Java, alleviates the conducting of proteogenomic analyses of bacteria. From a given genome sequence, a naïve six frame translation is performed and, if desired, a decoy database generated. This database is used to identify MS/MS spectra by common peptide identification algorithms. After combination of the search results and optional flagging for different experimental conditions, the results can be browsed and further inspected. In particular, for each peptide the number of identifications for each condition and the positions in the corresponding protein sequences are shown. Intermediate and final results can be exported into GFF3 format for visualization in common genome browsers. CONCLUSIONS: To facilitate proteogenomics analyses the Bacterial Proteogenomic Pipeline is a set of comprehensive tools running on common desktop computers, written in Java and thus platform independent. The pipeline allows integrating peptide identifications from various algorithms and emphasizes the visualization of spectral counts from different experimental conditions.
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spelling pubmed-42906072015-01-15 The bacterial proteogenomic pipeline Uszkoreit, Julian Plohnke, Nicole Rexroth, Sascha Marcus, Katrin Eisenacher, Martin BMC Genomics Research BACKGROUND: Proteogenomics combines the cutting-edge methods from genomics and proteomics. While it has become cheap to sequence whole genomes, the correct annotation of protein coding regions in the genome is still tedious and error prone. Mass spectrometry on the other hand relies on good characterizations of proteins derived from the genome, but can also be used to help improving the annotation of genomes or find species specific peptides. Additionally, proteomics is widely used to find evidence for differential expression of proteins under different conditions, e.g. growth conditions for bacteria. The concept of proteogenomics is not altogether new, in-house scripts are used by different labs and some special tools for eukaryotic and human analyses are available. RESULTS: The Bacterial Proteogenomic Pipeline, which is completely written in Java, alleviates the conducting of proteogenomic analyses of bacteria. From a given genome sequence, a naïve six frame translation is performed and, if desired, a decoy database generated. This database is used to identify MS/MS spectra by common peptide identification algorithms. After combination of the search results and optional flagging for different experimental conditions, the results can be browsed and further inspected. In particular, for each peptide the number of identifications for each condition and the positions in the corresponding protein sequences are shown. Intermediate and final results can be exported into GFF3 format for visualization in common genome browsers. CONCLUSIONS: To facilitate proteogenomics analyses the Bacterial Proteogenomic Pipeline is a set of comprehensive tools running on common desktop computers, written in Java and thus platform independent. The pipeline allows integrating peptide identifications from various algorithms and emphasizes the visualization of spectral counts from different experimental conditions. BioMed Central 2014-12-08 /pmc/articles/PMC4290607/ /pubmed/25521444 http://dx.doi.org/10.1186/1471-2164-15-S9-S19 Text en Copyright © 2014 Uszkoreit et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Uszkoreit, Julian
Plohnke, Nicole
Rexroth, Sascha
Marcus, Katrin
Eisenacher, Martin
The bacterial proteogenomic pipeline
title The bacterial proteogenomic pipeline
title_full The bacterial proteogenomic pipeline
title_fullStr The bacterial proteogenomic pipeline
title_full_unstemmed The bacterial proteogenomic pipeline
title_short The bacterial proteogenomic pipeline
title_sort bacterial proteogenomic pipeline
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4290607/
https://www.ncbi.nlm.nih.gov/pubmed/25521444
http://dx.doi.org/10.1186/1471-2164-15-S9-S19
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