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 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.基于质谱的蛋白质组学（mass-spectrometry-based proteomics）领域的近期进展，如今正推动针对蛋白质组（proteome）时空动态特征的前瞻性大规模研究。然而此类数据集的规模与复杂度持续攀升，已远超当前下游计算方法的处理能力，尤其是支撑定量后分析流程（postquantification analysis pipeline）的相关工具。本文提出HiQuant这一全新工具，可实现定量后分析流程的设计与执行，涵盖检测归一化（assay normalization）、分组、实验重复质量控制及统计分析等常规数据处理步骤。HiQuant还支持交互式热图分析，可直接将结果导出至两大主流网络分析平台Cytoscape与Gephi，助力大规模数据集的结果解读。该工具既可通过友好的图形用户界面运行，也支持命令行模式下的一键式全流程自动化操作。本研究通过分析一个大规模复杂相互作用组（interactome）绘制数据集，评估了HiQuant的性能，结果显示其运行速度较现有方法提升200倍。此外，本研究通过分析两类全蛋白质组定量数据验证了HiQuant的通用实用性：一类来自一项大规模公开的酪氨酸激酶（tyrosine kinase）小干扰RNA（siRNA）敲低研究，另一项为针对KSR1与KSR2相互作用组时空动态特征的内部研究。可访问http://hiquant.primesdb.eu下载HiQuant、示例数据集及配套文档。