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Efficient visualization of high-throughput targeted proteomics experiments: TAPIR


Röst, Hannes L; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars (2015). Efficient visualization of high-throughput targeted proteomics experiments: TAPIR. Bioinformatics, 31(14):2415-2417.

Abstract

Motivation: Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. Results: We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. Availability and implementation: TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. Contact: lars@imsb.biol.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online

Abstract

Motivation: Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. Results: We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. Availability and implementation: TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. Contact: lars@imsb.biol.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online

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Item Type:Journal Article, refereed, original work
Communities & Collections:National licences > 142-005
Dewey Decimal Classification:Unspecified
Language:English
Date:15 July 2015
Deposited On:15 Oct 2018 15:16
Last Modified:24 Sep 2019 23:38
Publisher:Oxford University Press
ISSN:1367-4803
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/bioinformatics/btv152
Related URLs:https://www.swissbib.ch/Search/Results?lookfor=nationallicenceoxford101093bioinformaticsbtv152 (Library Catalogue)
PubMed ID:25788625

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