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GraphMap specifications

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Unique identifier OMICS_16089
Name GraphMap
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input format FASTA/FASTQ
Biological technology Oxford Nanopore
Operating system Unix/Linux
License MIT License
Computer skills Advanced
Version 0.4.1
Stability Stable
Maintained Yes

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GraphMap citations

 (9)
library_books

Nanopore sequencing and assembly of a human genome with ultra long reads

2018
PMCID: 5889714
PMID: 29431738
DOI: 10.1038/nbt.4060

[…] generated by ultra-long reads do not fit in the bam format specification, necessitating the use of sam or cram formats only (https://github.com/samtools/hts-specs/issues/40). instead, we used graphmap to align ultra-long reads to grch38, which took >25k cpu hours (). software optimized for long reads, including ngm-lr and minimap2 (ref. ), were faster: minimap2 took 60 cpu hours. […]

library_books

Nanopore DNA Sequencing and Genome Assembly on the International Space Station

2017
PMCID: 5740133
PMID: 29269933
DOI: 10.1038/s41598-017-18364-0

[…] 30% of the reads mapped to each organism (fig. ). across all eight flow cells, approximately 10% of reads (n = 8,960) did not match to either lambda, e. coli, or mouse by direct alignment using graphmap and surpirt (figs  and ). this was attributed to single-read error rates of 8–20% on the r7 version of flow cells used, as the use of a more sensitive aligner (blastn, e-value cutoff = 10−8) […]

library_books

Nanopore sequencing enables near complete de novo assembly of Saccharomyces cerevisiae reference strain CEN.PK113 7D

2017
PMCID: 5812507
PMID: 28961779
DOI: 10.1093/femsyr/fox074

[…] (https://metrichor.com/s/). the error rate of nanopore reads in the cen.pk113–7d frankfurt and delft was determined by aligning them to the final cen.pk113–7d assembly (see section below) using graphmap (sović et al.) 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 […]

library_books

Rapid de novo assembly of the European eel genome from nanopore sequencing reads

2017
PMCID: 5543108
PMID: 28775309
DOI: 10.1038/s41598-017-07650-6

[…] it according to ont guidelines (https://github.com/nanoporetech/ont-assembly-polish). we first corrected nanopore-derived scaffolds with nanopore data using racon, based on alignments produced by graphmap version 0.3.0. ultimately racon sequence correction is performed by spoa, which is a partial order alignment algorithm that generates consensus sequences., subsequently, we used previously […]

library_books

Robust long read native DNA sequencing using the ONT CsgG Nanopore system

2017
PMCID: 5426553
PMID: 28503666
DOI: 10.21956/wellcomeopenres.12133.r21615

[…] ( ) to obtain the embedded fastq data. the respective fastq data were mapped to the reference human genome (grch38 primary assembly; genbank: gca_000001405.15) using graphmap (0.3.1; https://github.com/isovic/graphmap) ( ) with the --sensitive parameter enabled on a high performance computing cluster. high quality reads were mapped in 2d:17h using 14 threads. […]

library_books

Annotated mitochondrial genome with Nanopore R9 signal for Nippostrongylus brasiliensis

2017
PMCID: 5399971
PMID: 28491281
DOI: 10.5256/f1000research.11363.r19519

[…] minion reads were mapped to the assembled genome to identify variants not present in the wtsi reads., after remapping the original r9 minion reads back to the assembled and corrected genome with graphmap , four locations were found with variant calls that contributed to more than 50% of the read coverage. three of these variants involved transition mutations: t → c at 5742, g → a at 6102, […]


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GraphMap funding source(s)
Supported by the IMaGIN platform (project no. 102 101 0025), through a grant from the Science and Engineering Research Council, funding to the Genome Institute of Singapore from the Agency for Science, Technology and Research (A*STAR), Singapore, and funding from the Croatian Science Foundation (Project no. 7353—Algorithms for Genome Sequence Analysis).

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