Rapid evaluation and quality control of next generation sequencing data with FaQCs

Area of Science:

• Genomics
• Bioinformatics

Background:

• Next-generation sequencing (NGS) technologies generate vast amounts of data, revolutionizing genomic research.
• Sequencing read quality can degrade during processing, impacting downstream analyses.
• Early identification and mitigation of sequencing errors are crucial for reliable results.

Purpose of the Study:

• To introduce a novel software, FastQ Quality Control Software (FaQCs), for rapid processing and quality control of NGS data.
• To optimize processing speed and memory footprint for large-scale genomic datasets.

Main Methods:

• Algorithmic and parallel processing solutions were employed to enhance speed and reduce memory usage.
• FaQCs monitors sequencing run quality and removes poor-quality data.
• Automated PDF output provides side-by-side comparisons of original and trimmed data.

Main Results:

• FaQCs demonstrates improved processing speed and efficiency compared to existing solutions.
• The software facilitates better data analysis, leading to increased read recruitment to references.
• Enhanced single nucleotide polymorphism identification and de novo sequence assembly metrics were observed.

Conclusions:

• FaQCs integrates multiple functionalities into a user-friendly platform, including PhiX control filtering and FASTQ format conversion.
• Multi-threading and comprehensive graphical reporting aid in data quality control and assurance.
• The software provides a streamlined approach to managing and assuring the quality of NGS data.