Efficient visualization of high-throughput targeted proteomics experiments: TAPIR

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


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Graphics
  • Mass Spectrometry*
  • Proteomics / methods*
  • Software*