LongReadSum: A fast and flexible quality control and signal summarization tool for long-read sequencing data

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Existing quality control (QC) tools for sequencing data primarily focus on short reads, with limited options for long reads.
• Current long-read QC tools lack comprehensive metrics, cross-platform compatibility (PacBio, Oxford Nanopore, Illumina Complete Long Read), and support for various data formats (ONT POD5, FAST5, PacBio BAM).
• There is a need for tools that can handle large data volumes from platforms like Oxford Nanopore PromethION and provide specific insights like basecall signal and methylation information.

Purpose of the Study:

• To develop a fast, multi-threaded computational tool, LongReadSum, for comprehensive quality control of long-read sequencing data.
• To address the limitations of existing tools by supporting multiple sequencing platforms and data formats.
• To provide advanced QC features, including basecall signal intensity and base modification (methylation) analysis.

Main Methods:

• Developed LongReadSum as a multi-threaded C++ application.
• Integrated support for major long-read sequencing platforms (PacBio, Oxford Nanopore, Illumina Complete Long Read) and data formats (ONT POD5, FAST5, PacBio BAM).
• Implemented QC metrics covering read length, base quality, alignment, base modification, and Oxford Nanopore basecalling signal intensity.

Main Results:

• LongReadSum provides fast and comprehensive QC reports for long-read sequencing data.
• The tool successfully analyzes diverse data types including cDNA, direct mRNA, reduced representation methylation sequencing (RRMS), and whole genome sequencing (WGS).
• Demonstrated capability to handle large datasets, such as those generated by Oxford Nanopore PromethION flowcells.

Conclusions:

• LongReadSum effectively addresses the need for robust and efficient quality control in long-read sequencing.
• The tool enhances data analysis across various long-read platforms and applications, including methylation analysis.
• This provides a valuable resource for researchers working with large-scale genomic data from next-generation sequencing technologies.