RabbitQC-X

A unified, cross-platform quality control tool for sequencing data that supports both x86 and Sunway architectures.

Overview

RabbitQC-X combines two high-performance implementations:

• x86 Platform: RabbitQCPlus - optimized for x86 architecture with AVX2/AVX512 support
• Sunway Platform: SWQC - optimized for Sunway supercomputer architecture with heterogeneous computing

If you encounter issues with RabbitQC-X in your environment, you can always fall back to the original standalone projects:

• Original RabbitQCPlus (x86): RabbitBio/RabbitQCPlus
• Original SWQC (Sunway): RabbitBio/SWQC

These upstream projects are kept as close as possible to their original behavior; RabbitQC-X focuses on unifying the build and code layout.

Features

x86 Platform (RabbitQCPlus)

• Single-threaded performance improved by 2x
• 4x+ speedup for gzip-compressed files compared to SOAPnuke
• Integrated and optimized CARE error correction engine (1.3x speedup)
• Automatic instruction set detection (AVX2/AVX512)
• Support for both NGS and TGS data

Sunway Platform (SWQC)

• First distributed quality control software for Sunway platform
• 1.5-3x faster than fastest x86 software on single node
• 65%-80% scalability on 16 nodes
• Optimized multi-threaded (de)compression framework

Installation

System Requirements

For x86 Platform:

• 64-bit Linux system
• GCC 7.5.0 or newer (GCC 9.0+ recommended for best performance)
• zlib library
• OpenMP support

For Sunway Platform:

• Sunway next-generation platform
• sw9gcc 7.1.0 or newer
• zlib library
• MPI support

Building from Source

1. Clone the repository

git clone <repository-url>
cd RabbitQC-X

2. Build for x86 platform

mkdir build
cd build
cmake -DPLATFORM=x86 ..
make -j4

3. Build for Sunway platform

mkdir build-sunway
cd build-sunway
cmake -DPLATFORM=sunway ..
make -j8

Project Structure

RabbitQC-X/
├── src/                 # Unified entry point
│   ├── main.cpp        # Unified main program (platform-specific via #ifdef)
│   └── CLI11.hpp       # Command-line parsing library
├── common/              # Shared code between platforms
│   ├── lib/            # Unified library files (merged from both platforms)
│   ├── include/        # Shared header files
│   ├── common.hpp
│   ├── exceptions.hpp
│   └── system.h
├── x86/                 # x86 platform specific code
│   ├── src/            # x86 source files
│   ├── include/        # x86 header files
│   ├── dependencies/   # Third-party dependencies (Thrust)
│   └── CMakeLists.txt
├── sunway/             # Sunway platform specific code
│   ├── src/            # Host source files
│   ├── slave/          # Slave core source files
│   └── CMakeLists.txt
├── CMakeLists.txt      # Top-level CMake configuration
└── README.md           # This file

Usage

For Next Generation Sequencing (NGS) Data

Single-end (SE) reads

# Plain FASTQ
./rabbitqc-x -w 8 -i in1.fastq -o p1.fastq

# Gzip compressed
./rabbitqc-x -w 8 -i in1.fastq.gz -o p1.fastq.gz

Paired-end (PE) reads

# Plain FASTQ
./rabbitqc-x -w 8 -i in1.fastq -I in2.fastq -o p1.fastq -O p2.fastq

# Gzip compressed
./rabbitqc-x -w 16 -i in1.fastq.gz -I in2.fastq.gz -o p1.fastq.gz -O p2.fastq.gz

With error correction (x86 only)

# SE mode
./rabbitqc-x -w 32 -i in1.fastq -o p1.fastq --correctWithCare --coverage 30 --pairmode SE

# PE mode
./rabbitqc-x -w 32 -i in1.fastq -I in2.fastq -o p1.fastq -O p2.fastq --correctWithCare --coverage 30 --pairmode PE

For Third Generation Sequencing (TGS) Data (x86 only)

# Plain FASTQ
./rabbitqc-x -w 4 -i in.fastq --TGS

# Gzip compressed
./rabbitqc-x -w 6 -i in.fastq.gz --TGS

Command-line Options

For complete help information:

./rabbitqc-x -h

Common options:

• -w, --thread: Number of threads to use
• -i, --in1: Input file 1 (or single-end file)
• -I, --in2: Input file 2 (for paired-end)
• -o, --out1: Output file 1 (or single-end file)
• -O, --out2: Output file 2 (for paired-end)
• --TGS: Enable TGS mode (third-generation sequencing)
• --correctWithCare: Enable CARE error correction (x86 only)

Performance

The x86 version has been benchmarked against RabbitQC (v0.0.1), fastp (v0.23.2), SOAPnuke (v2.1.7), Trimmomatic (v0.40), and CARE (v2.0.0) using 370 million Illumina sequencing reads.

Key results:

• Significant speedup on both plain and gzip-compressed FASTQ files
• Improved performance for over-representation analysis (5x faster)
• Efficient error correction with CARE engine integration

Visual Output

The tool generates comprehensive HTML reports with before/after filtering statistics. See example reports for detailed visualization of quality control metrics.

License

See LICENSE files in respective platform directories.

Citation

For x86 Platform (RabbitQCPlus):

Lifeng Yan, Zekun Yin, Hao Zhang, Zhan Zhao, Mingkai Wang, André Müller, Felix Kallenborn et al. "RabbitQCPlus 2.0: More efficient and versatile quality control for sequencing data." Methods 216 (2023): 39-50.

Lifeng Yan, Zekun Yin, Hao Zhang, Zhan Zhao, Mingkai Wang, André Müller, Robin Kobus, Yanjie Wei, Beifang Niu, Bertil Schmidt, Weiguo Liu. "RabbitQCPlus: More Efficient Quality Control for Sequencing Data," 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Las Vegas, NV, USA, 2022, pp. 619-626, doi: 10.1109/BIBM55620.2022.9995332.

Zekun Yin, Hao Zhang, Meiyang Liu, Wen Zhang, Honglei Song, Haidong Lan, Yanjie Wei, Beifang Niu, Bertil Schmidt, Weiguo Liu, RabbitQC: High-speed scalable quality control for sequencing data, Bioinformatics, , btaa719, https://doi.org/10.1093/bioinformatics/btaa719

For Sunway Platform (SWQC):

Yan L, Yin Z, Zhang T, et al. SWQC: Efficient sequencing data quality control on the next-generation sunway platform[J]. Future Generation Computer Systems, 2025, 164: 107577.

Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

Contact

For questions and support, please open an issue in the repository.