Efficient visualization of high-throughput targeted proteomics experiments: TAPIR

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:...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Bioinformatics Jg. 31; H. 14; S. 2415 - 2417
Hauptverfasser: Röst, Hannes L., Rosenberger, George, Aebersold, Ruedi, Malmström, Lars
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England 15.07.2015
Schlagworte:
Bioinformatics
Computer Graphics
Computer programs
Format
Licenses
Mass Spectrometry
Proteins
Proteomics
Proteomics - methods
Software
Visualization
ISSN:1367-4803, 1367-4811, 1460-2059
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1367-4803
1367-4811
1460-2059
DOI:10.1093/bioinformatics/btv152