Related Experiment Video
Updated: Mar 22, 2026
11:26
Sequencing of mRNA from Whole Blood using Nanopore Sequencing
Published on: June 3, 2019
14.9K
Fast and sensitive mapping of nanopore sequencing reads with GraphMap
Ivan Sović1,2, Mile Šikić3,4, Andreas Wilm1
1Computational &Systems Biology, Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore 138672, Singapore.
Nature Communications
|April 16, 2016
Summary
GraphMap is a new bioinformatics tool that accurately maps nanopore sequencing reads, improving variant detection and pathogen identification for genomic analysis.
Area of Science:
- Bioinformatics
- Genomics
- Molecular Biology
Background:
- Nanopore sequencing offers democratic access to genomic data but presents unique error profiles.
- Existing bioinformatics tools struggle with the high error rates characteristic of nanopore reads.
Purpose of the Study:
- To develop a novel mapping algorithm, GraphMap, specifically designed for analyzing nanopore sequencing data.
- To enhance the accuracy and efficiency of aligning long, potentially error-rich nanopore reads.
Main Methods:
- GraphMap employs a progressive alignment refinement strategy.
- It utilizes fast graph traversal for efficient alignment of long reads.
- Algorithm performance was evaluated against established short- and long-read mappers using MinION sequencing datasets.
Main Results:
- GraphMap demonstrates high precision (>95%) and mapping sensitivity improvements of 10-80% compared to other mappers.
- It successfully maps over 95% of bases from nanopore reads.
- Enabled 15% increased sensitivity in single-nucleotide variant calling and precise detection of structural variants (100 bp to 4 kbp).
Conclusions:
- GraphMap effectively addresses the challenges of nanopore sequencing error rates.
- The algorithm enhances genomic variant analysis and pathogen identification capabilities.
- GraphMap provides a robust and efficient solution for nanopore read mapping, advancing genomic research.
