RNA-QC-chain: comprehensive and fast quality control for RNA-Seq data

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Next-generation sequencing (NGS) technologies, particularly RNA sequencing (RNA-Seq), are widely used in biological research.
• Raw RNA-Seq data quality issues can lead to inaccurate analytical outcomes and flawed conclusions.
• Current RNA-Seq data quality control (QC) often involves multiple tools, resulting in inefficiency.

Purpose of the Study:

• To develop a comprehensive, efficient, and user-friendly quality control (QC) pipeline specifically for RNA-Seq data.
• To address the limitations of existing QC methods by integrating multiple essential steps into a single package.
• To improve the accuracy and reliability of downstream RNA-Seq analyses.

Main Methods:

• Development of RNA-QC-Chain, a pipeline integrating sequencing quality assessment, trimming, contamination filtering (rRNA and foreign species), and alignment statistics reporting.
• Extension of a general NGS QC tool (QC-Chain) with RNA-Seq specific features like automatic rRNA detection and contaminating species identification.
• Implementation of parallel computing and optimizations for enhanced processing speed and efficiency.

Main Results:

• RNA-QC-Chain provides a comprehensive suite of QC functionalities for RNA-Seq data.
• The pipeline offers features such as RNA sequence trimming, automatic rRNA detection, and contaminating species identification.
• Evaluations demonstrated superior performance in terms of functional versatility and processing speed compared to existing tools.

Conclusions:

• RNA-QC-Chain effectively and efficiently resolves quality control processes for RNA-Seq data.
• The tool enhances usability, running time, file management, and result interpretability in RNA-Seq QC.
• RNA-QC-Chain represents a significant advancement in ensuring the quality of RNA-Seq data for reliable biological insights.