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Bioinformatics. 2015 Jul 15;31(14):2415-7. doi: 10.1093/bioinformatics/btv152. Epub 2015 Mar 18.

Efficient visualization of high-throughput targeted proteomics experiments: TAPIR.

Author information

1
ETH Zurich, Institute of Molecular Systems Biology, CH-8093 Zurich, Switzerland and Ph.D. Program in Systems Biology, University of Zurich and ETH Zurich, CH-8057 Zurich, Switzerland.
2
ETH Zurich, Institute of Molecular Systems Biology, CH-8093 Zurich, Switzerland and.

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.

PMID:
25788625
DOI:
10.1093/bioinformatics/btv152
[Indexed for MEDLINE]
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