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.