From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy

Area of Science:

• Genomics and Bioinformatics
• Molecular Biology

Background:

• Nanopore sequencing is an emerging technology providing real-time, long-read sequencing on portable devices at low cost.
• Despite its advantages, nanopore sequencing is characterized by a high error rate, typically between 5% and 15%, even with recent improvements.

Purpose of the Study:

• To review computational approaches for determining the error rate of nanopore sequencing.
• To outline strategies for improving nanopore sequencing data quality.

Main Methods:

• Literature review of computational methods for nanopore sequencing error rate assessment.
• Analysis of strategies for raw data processing, including base calling and consensus sequence generation.

Main Results:

• Identified and categorized various computational tools and algorithms used to quantify nanopore sequencing errors.
• Highlighted methods for base modification detection and consensus sequence generation from noisy nanopore data.

Conclusions:

• Computational methods are crucial for accurately assessing and mitigating the high error rates in nanopore sequencing.
• Effective data processing strategies can translate raw nanopore reads into reliable base calls, enabling diverse research applications and base modification detection.