Merging High-Throughput, Amplicon-Based Second and Third Generation Sequencing Data: An Integrative and Modular Data...

Area of Science:

• Genomics
• Bioinformatics

Background:

• Second-generation sequencing (Illumina) offers high accuracy but struggles with complex genomic regions.
• Third-generation sequencing (ONT) provides long reads but has lower accuracy.
• Phased haplotype derivation from amplicon-based NGS data is challenging and requires significant bioinformatics expertise.

Purpose of the Study:

• To develop an integrative, open-access, modular data-analysis framework.
• To combine the strengths of short and long sequencing reads for improved genomic analysis.
• To automate the processing of high-throughput sequencing data from both Illumina and ONT platforms.

Main Methods:

• Constructed an integrative, open-access modular data-analysis framework.
• Automated processing of high-throughput sequencing data from second (Illumina) and third generation (ONT) platforms.
• Validated framework performance using synthetic and real-life data, including analysis of FUT1/2/3 sequencing data from 400 blood donors.

Main Results:

• The framework successfully integrates data from both sequencing platforms, leveraging their respective strengths.
• Automated evaluation and color-coding of variant information highlight discrepancies.
• Haplotypes are efficiently listed by frequency, simplifying analysis.
• Individual modules of the framework can be used independently.

Conclusions:

• The developed framework offers an automated and efficient solution for analyzing complex genomic regions.
• It enhances variant accuracy and simplifies phased haplotype derivation.
• The integrative approach overcomes limitations of individual sequencing technologies, providing a powerful tool for genomic research.