HiQuant: Rapid postquantification analysis of large-scale MS-generated proteomics data

Kenneth Bryan, Mohamed-Ali Jarboui, Raso Cinzia, Manuel Bernal-Llinares, Bredan McCann, Jens Rauch, Karsten Bodlt, David Lynn

    Research output: Contribution to journalArticle

    4 Citations (Scopus)


    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.

    Original languageEnglish
    Pages (from-to)2072-2079
    Number of pages8
    JournalJournal of Proteome Research
    Issue number6
    Publication statusE-pub ahead of print - 2016

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    Bryan, K., Jarboui, M-A., Cinzia, R., Bernal-Llinares, M., McCann, B., Rauch, J., Bodlt, K., & Lynn, D. (2016). HiQuant: Rapid postquantification analysis of large-scale MS-generated proteomics data. Journal of Proteome Research, 15(6), 2072-2079. https://doi.org/10.1021/acs.jproteome.5b01008