HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically...

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Bibliographic Details
Published in:Journal of proteome research 2016-06, Vol.15 (6), p.2072-2079
Main Authors: Bryan, Kenneth, Jarboui, Mohamed-Ali, Raso, Cinzia, Bernal-Llinares, Manuel, McCann, Brendan, Rauch, Jens, Boldt, Karsten, Lynn, David J
Format: Article
Language:English
Subjects:
Animals
Computational Biology
Data Interpretation, Statistical
Humans
Mass Spectrometry - methods
Protein Interaction Mapping
Protein Kinases
Protein-Serine-Threonine Kinases
Proteome
Proteomics - methods
Software
Workflow
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Summary:Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant’s performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant’s general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu.
ISSN:1535-3893
1535-3907
DOI:10.1021/acs.jproteome.5b01008