qPCRtools C++ Version

A cross-platform desktop application for qPCR data analysis, rewritten in C++ from the R package qPCRtools.

Download

Pre-built binaries are available for download from GitHub Releases

• Windows: qPCRtools-windows.zip - Extract and run qPCRtools.exe
• macOS: qPCRtools-macos.dmg - Open DMG and drag qPCRtools.app to Applications

No installation required! Just download and run.

Features

• Modern Web-based Interface

  • Built with Qt6 QWebEngineView
  • Responsive design using Bootstrap 5.3
  • Interactive charts powered by ECharts
  • Bilingual support (Chinese/English)
  • Clean, modern UI inspired by ggplot2 aesthetics

• Multiple Analysis Methods

  • Standard Curve Calculation
  • ΔCt (Delta Ct) Method
  • ΔΔCt (Delta-Delta Ct) Method

• Data Import

  • CSV/TXT file support
  • Excel (.xlsx) file support (planned)
  • Interactive data preview
  • Example data for quick start

• Statistical Analysis

  • t-test (independent and paired)
  • Wilcoxon test (rank-sum and signed-rank)
  • ANOVA with Tukey's HSD
  • Outlier detection (IQR method)

• Visualization

  • ggplot2-style charts
  • Standard curve plots
  • Box plots
  • Bar plots with error bars
  • Significance labels
  • Multiple color palettes

• Multi-language Support

  • 中文 (Chinese)
  • English

Usage

Quick Start with Example Data

Try qPCRtools with built-in example data:

1. Download and extract the pre-built application
2. Launch qPCRtools
3. Click "Load Example Data" to load sample qPCR data
4. Select analysis method and click "Run Analysis"

Or manually load example files from the examples/ directory:

• examples/cq.csv - Cq values from qPCR experiment
• examples/design.csv - Experimental design mapping

Using Your Own Data

1. Import Data

   • Load Cq data file (CSV format)
   • Load experimental design file (optional)
   • Preview data in the table

2. Configure Analysis

   • Select analysis method (Standard Curve, ΔCt, ΔΔCt)
   • Set reference gene and control group
   • Choose statistical test method
   • Configure visualization options

3. Run Analysis

   • Click "Run Analysis" button
   • View results in multiple tabs:
     • Data Table: Expression values
     • Charts: ggplot2-style visualizations
     • Statistics: Test results with p-values

4. Export Results

   • Export charts as images
   • Export data tables
   • Export statistical results

Project Structure

qPCRtools_cpp/
├── CMakeLists.txt           # Main CMake configuration
├── README.md                # This file
├── src/                     # Source files
│   ├── Core/                # Core algorithms
│   │   ├── StandardCurve.cpp
│   │   ├── ExpressionCalculator.cpp
│   │   └── StatisticalTest.cpp
│   ├── Data/                # Data structures and parsers
│   │   ├── DataFrame.cpp
│   │   ├── CSVParser.cpp
│   │   └── ExcelImporter.cpp
│   ├── GUI/                 # User interface
│   │   ├── WebMainWindow.cpp
│   │   └── WebBridge.cpp
│   └── Utils/               # Utility functions
├── include/                 # Header files
│   ├── Core/
│   ├── Data/
│   ├── GUI/
│   └── Utils/
├── web/                     # Web interface files
│   ├── index.html           # Main HTML
│   ├── css/
│   │   └── style.css        # Stylesheets
│   └── js/
│       ├── app.js           # Application logic
│       ├── i18n.js          # Internationalization
│       ├── jquery.min.js
│       ├── bootstrap.bundle.min.js
│       └── echarts.min.js   # Chart library
├── examples/                # Example data files
│   ├── cq.csv              # Sample Cq data
│   ├── design.csv          # Sample experimental design
│   └── README.md           # Example data documentation
└── translations/            # i18n translation files

Building from Source

If you prefer to build from source or contribute to development:

Build Dependencies

• CMake >= 3.20
• C++17 compiler (MSVC 2019+, GCC 10+, Clang 12+)
• Qt6 >= 6.5 (Core, Widgets, WebEngineWidgets, WebChannel)
• Eigen3 >= 3.4
• GSL (GNU Scientific Library) >= 2.7 (optional)

Platform-Specific Setup

macOS

# Install dependencies via Homebrew
brew install cmake qt@6 eigen gsl

Windows

• Install Qt6 from the official installer
• Install Visual Studio 2019 or later
• Install CMake from the official website

📖 Detailed Windows build guide: See WINDOWS_BUILD.md for step-by-step instructions.

Linux (Ubuntu/Debian)

sudo apt-get update
sudo apt-get install cmake qt6-base-dev qt6-webengine-dev libeigen3-dev libgsl-dev

Build Instructions

# Clone repository
git clone https://github.com/lixiang117423/qPCRtools_cpp.git
cd qPCRtools_cpp

# Create build directory
mkdir build && cd build

# Configure with CMake
cmake ..

# Build
cmake --build . --parallel

# Run the application
./qPCRtools  # macOS/Linux
# or
qPCRtools.exe  # Windows

Citation

If you use this software in your research, please cite:

Li X, Wang Y, Li J, et al. qPCRtools: An R package for qPCR data processing and visualization. Frontiers in Genetics, 2022, 13: 1002704.

DOI: 10.3389/fgene.2022.1002704

📄 Full article: https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.1002704/full

BibTeX:

@article{li2022qpcrtools,
  title={qPCRtools: An R package for qPCR data processing and visualization},
  author={Li, Xiang and Wang, Yan and Li, Jun and Li, Xueying and Zhang, Yage and Zhang, Yinping and Wang, Ji-Hong},
  journal={Frontiers in Genetics},
  volume={13},
  pages={1002704},
  year={2022},
  publisher={Frontiers Media SA},
  doi={10.3389/fgene.2022.1002704}
}

License

MIT License - see LICENSE file for details

Authors

• Xiang LI (lixiang117423@gmail.com)

Acknowledgments

This is a C++ reimplementation of the original R package qPCRtools.