Overview

HiQuant automates the post-quantification analysis of Mass Spectrometry (MS) generated proteomics data especially those involving additional experimental variables (e.g. labels, replicates, time points and treatments). HiQuant eliminates the laborious, manual processing of large protein quantification datasets typical of spreadsheet-based applications (Video 1 below) and reduces the potential for data handling variation and human error. HiQuant imports a plain text quantification file (e.g. MaxQuant proteinGroups.txt) and supports the user in defining and implementing a workflow, encompassing data filtering, replicate grouping, label reversal, data transformation and significance testing (Video 2 and Video 5). Once parameters HiQuant have been configured they may be saved as a config file for later use (Video 3) or may be used to support a one touch command line mode (Video 4). HiQuant also supports preliminary identification of outlying replicates and subsequent interactive result visualization. With HiQuant the user can rapidly optimize workflow parameters and generally gain a greater level of control over the analysis of large protein quantification datasets. HiQuant results may be visualized directly via an interactive heatmap that can be exported to high quality PDF. Results can also be exported to Cytoscape (.xgmml) or Gephi (.gexf) graph formats (Video 6) supporting large datasets that can be interpreted in this manner (e.g. interactome studies).

 

Downloads

Download 1: HiQuant (Win)
Download 2: HiQuant (Mac)
Download 3: HiQuant (Java JAR)
Download 4: User Manual
Download 5: Demo Datasets

HiQuant (GUI Mode):
HiQuant (GUI Mode) may be downloaded as an application for Windows or MacOS. These applications may need to be given permissions to run depending on local system settings. MacOS Note: The error "hiquant.app file is damaged and can't be opened." means one needs to change system security settings to allow all .apps to run. Windows Note: After downloading make sure to first extract (unzip) the download folder before running the hiquant.exe file otherwise demo data files will not be readable (and a file read error message will appear).

HiQuant Quick Demo (GUI Mode):
Download the folder containing HiQuant, extract files and start the hiquant.app or hiquant.exe. Load one of the '.config' files in the data sub-folder via File > Load Configuration file... (see Video 3 below and HiQuant user manual) when the parameters are populated go to the Analyze tab and hit 'Run Analysis' (takes between 15-45 seconds depending on the demo config file chosen) and then hit 'Generate Visualization' to view results (via the default heatmap view).

HiQuant Runnable JAR (GUI or Command Line Mode):
If JVM parameters need to be customized (e.g. if more RAM is needed) or if the system specific applications fail to run, the cross platform HiQuant Runnable JAR file (Download 3 only) may be downloaded and run directly on the command line (Windows) or the terminal (MacOS, Linux) by running the command "java -Xmx2000m -jar hiquant.jar" in the folder containing the hiquant.jar file.
The HiQuant Runnable JAR file may also be used to fully automate the HiQuant analysis pipeline via the Command Line Mode. This can be executed by providing an additional plain text '.config' file as an argument e.g. "java -Xmx2000m -jar hiquant.jar myParams.config". See Videos 3 and 4 below (and the HiQuant User Manual) to create and execute a '.config' file respectively.

 

HiQuant Analysis of Protein Quantification Data Compared the Current Manual Approach

Video 1:
Analysis with Perseus

1 Bait Experiment (AP-MS SILAC)
Perseus analysis of proteinGroups.txt file containing 36 assays relating to a AP-MS experiment using SRC as the bait protein. Assays consist of technical (x2) and biological (x3) replicates, tiplex SILAC, reverse labelling and two cell types. Peseus analysis involves extensive manual 'point and click' operations and takes and expert user approximatley 20 minutes to complete. This method is also more prone to human error and user variation. Furthermore, manual analysis is not scalable as, unlike HiQuant, the workflow configuration cannot be saved (see Video 3) or run over multiple experiments (see Video 4).

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Video 2:
HiQuant Configuration and Analysis

1 Bait Experiment (AP-MS SILAC)

Analysis of proteinGroups.txt file containing 36 assays relating to a AP-MS experiment using SRC as the bait protein. Assays consist of technical (x2) and biological (x3) replicates, tiplex SILAC, reverse labelling and two cell types. The HiQuant Graphical User Interface is first used to set analysis parameters and then to run a complete analysis producing the list of signficantly changing (interacting) prey protein. When parameters are set the configuration can be saved and reloaded gain a 10-fold speed-up (or around 200-fold compared to Perseus). For further details see the detailed tutorials (below) or download the HiQuant User Manual in the downloads section.

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Video 3:
HiQuant Analysis (with .config file)

1 Bait Experiment (AP-MS SILAC)

Analysis of same dataset above (SRC bait prey "proteinGroups.txt" file) except for re-use of configuration file to set parameters which lends signficant speed up to analysis time. This confugration file can also be used to run HiQuant on the command line (see 'Automated Batch Analysis 'below) For further details see the detailed tutorials (below) or download the HiQuant User Manual in the downloads section.

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HiQuant Detailed Tutorial and Added Features

Video 6:
HiQuant Network File Analysis with Gephi

1 Bait x 5 time points
Results can be viewed directly in HiQuant via the heatmap feature or can be exported to graph format where appropriate (e.g. interactome networks). HiQuant supports the two main graph analysis platfroms formats in Biology (Cytoscapes's xgmml format) and Network Analysis (Gephi's gexf format). The following is a brief tutorial on how to use Gephi to layout and format your HiQuant exported gexf file to achieve a publication quality visualization. For further details see the HiQuant User Manual in the downloads section.

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