# Fast and sensitive mapping of error-prone nanopore sequencing reads with GraphMap

## TL;DR

GraphMap is a new tool for nanopore sequencing that improves accuracy and sensitivity in mapping reads, enabling better variant detection and pathogen identification.

## Contribution

GraphMap introduces a novel read-funneling paradigm and fast graph traversal for nanopore read mapping with high precision and sensitivity.

## Key findings

- GraphMap increases mapping sensitivity by 15-80% compared to other mappers.
- GraphMap achieves consensus calling with <1 error in 100,000 bases.
- It improves variant calling sensitivity by 76% over BWA-MEM and detects structural variants precisely.

## Abstract

Exploiting the power of nanopore sequencing requires the development of new bioinformatics approaches to deal with its specific error characteristics. We present the first nanopore read mapper (GraphMap) that uses a read-funneling paradigm to robustly handle variable error rates and fast graph traversal to align long reads with speed and very high precision (>95%). Evaluation on MinION sequencing datasets against short and long-read mappers indicates that GraphMap increases mapping sensitivity by at least 15-80%. GraphMap alignments are the first to demonstrate consensus calling with <1 error in 100,000 bases, variant calling on the human genome with 76% improvement in sensitivity over the next best mapper (BWA-MEM), precise detection of structural variants from 100bp to 4kbp in length and species and strain-specific identification of pathogens using MinION reads. GraphMap is available open source under the MIT license at https://github.com/isovic/graphmap.