GTZ: a fast compression and cloud transmission tool optimized for FASTQ files.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• DNA sequencing generates massive datasets, demanding efficient storage and transmission solutions.
• Current data sharing methods face challenges with speed, cost, and bandwidth limitations.
• Cloud storage necessitates optimized tools for handling large-scale sequencing data.

Purpose of the Study:

• To introduce GTZ, a novel compression and transmission tool for FASTQ files.
• To address the need for faster, cheaper, and more efficient sequencing data sharing.
• To facilitate the integration of genomic data into cloud computing environments.

Main Methods:

• GTZ employs a reference-free, lossless compression approach for FASTQ files.
• It utilizes adaptive context modeling and arithmetic coding for efficient data compression.
• The tool supports local saving or direct transmission of compressed data to cloud storage.

Main Results:

• GTZ demonstrates superior performance in compression ratio, speed, and stability compared to other tools.
• The tool effectively compresses multiple FASTQ files or directories simultaneously.
• Evaluations on diverse FASTQ benchmarks confirm GTZ's efficiency.

Conclusions:

• GTZ provides efficient lossless compression and simultaneous cloud transmission for FASTQ data.
• It is a valuable tool for next-generation sequencing (NGS) data storage and cloud-based transmission.
• GTZ is freely accessible, promoting its adoption in bioinformatics workflows.