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

作者：Bryan Kenneth; Jarboui Mohamed Ali; Raso Cinzia; Bernal Llinares Manuel; McCann Brendan; Rauch Jens; Boldt Karsten; Lynn David J

来源：Journal of Proteome Research, 2016, 15(6): 2072-2079.

DOI：10.1021/acs.jproteome.5b01008

• bioinformatics
• proteomics
• software
• mass spectrometry
• data analysis
• protein quantification
• visualization
• network analysis
• high-dimensional 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 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.

• 出版日期2016-6