RabbitV

RabbitV: Unique k-mer–based pathogen detection from Illumina sequencing data

RabbitV detects and identifies viruses and microorganisms in Illumina sequencing datasets using rapid unique k-mer analysis optimized for large-scale data processing.

Key Features:

• Unique k-mer Identification: Performs fast generation and querying of unique k-mers (RabbitUniq) to detect viral and microbial sequences with high speed and accuracy.
• High-Performance Computing Optimization: Utilizes multi-threading, vectorization, and fast data parsing on multi-core CPUs to accelerate unique k-mer generation (42.5× faster than fastv) and pathogen identification (14.4× faster than fastv).
• Large-Scale Dataset Processing: Processes extensive FASTQ datasets (e.g., 255 GB across 40 COVID-19 samples) within 320 seconds.

Scientific Applications:

• Pathogen Diagnosis: Enables rapid detection of viruses and microorganisms for infectious disease analysis.
• Microbial and Viral Research: Supports large-scale studies of microbial communities and viral evolution through efficient sequencing data analysis.

Methodology:

Implements high-speed identification and comparison of unique k-mers as pathogen-specific molecular signatures, leveraging parallelized computation and vectorized processing to scan Illumina FASTQ sequencing data for viral and microbial sequences.