Fast and sensitive mapping of nanopore sequencing reads with GraphMap

Abstract

Realizing the democratic promise of nanopore sequencing requires the development of new bioinformatics approaches to deal with its specific error characteristics. Here we present GraphMap, a mapping algorithm designed to analyse nanopore sequencing reads, which progressively refines candidate alignments to robustly handle potentially high-error rates and a fast graph traversal to align long reads with speed and high precision (>95%). Evaluation on MinION sequencing data sets against short- and long-read mappers indicates that GraphMap increases mapping sensitivity by 10–80% and maps >95% of bases. GraphMap alignments enabled single-nucleotide variant calling on the human genome with increased sensitivity (15%) over the next best mapper, precise detection of structural variants from length 100 bp to 4 kbp, 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.

Nanopore sequencing enables near-completede novoassembly ofSaccharomyces cerevisiaereference strain CEN.PK113-7D

“…Genomic DNA of CEN.PK113-7D Delft and CEN.PK113-7D Frankfurt for WGS was isolated using the Qiagen 100/G kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions and quantified using a Qubit R Fluorometer 2.0 (ThermoFisher Scientific, Waltham, MA, USA). (Sović et al 2016) and calculating mismatches based on the CIGAR strings of reads with a mapping quality of at least 1 and no more than 500 nt of soft/hard clipping on each end of the alignment to avoid erroneous read alignments due to repetitive regions (i.e. paralogous genes, genes with copy number variation).…”

“…Raw nanopore reads were filtered for lambda DNA by aligning to the Enterobacteria phage lambda reference genome (RefSeq assembly accession: GCF 000840245.1) using Graphmap (Sović et al 2016) with -no-end2end parameter and retaining only unmappeds reads using Samtools (Li et al 2009). All reads obtained from the Delft and the Frankfurt CEN.PK113-7D stock cultures were assembled de novo using Canu (version 1.3) (Koren et al 2017) with -genomesize set to 12 Mbp.…”

Beyond Homopolymer Errors: a Systematic Investigation of Nanopore-based DNA Sequencing Characteristics Using HLA-DQA2

“…4) was performed with Graphmap [10] and the BurrowsWheeler Aligner with the option -x ont2d (BWA-MEM) [11]. The former was found to align reads faster and with fewer mismatches (Fig.…”

Fast and memory-efficient noisy read overlapping with KD-trees

“…As a consequence, multiple programs were developed to efficiently overlap long noisy reads, such as BLASR (Chin et al, 2013), DALIGNER (Myers, 2014), MHAP (Berlin et al, 2015), GraphMap (Sović et al, 2016), and Minimap (Li, 2016). These all search for shared seeds between reads, but differ in the way these seeds are found and thereafter used to determine overlap candidates.…”