Abstract

Speed, single-base sensitivity and long read lengths make nanopores a promising technology for high-throughput sequencing. We evaluated and optimized the performance of the MinION nanopore sequencer using M13 genomic DNA and used expectation maximization to obtain robust maximum-likelihood estimates for insertion, deletion and substitution error rates (4.9%, 7.8% and 5.1%, respectively). Over 99% of high-quality 2D MinION reads mapped to the reference at a mean identity of 85%. We present a single-nucleotide-variant detection tool that uses maximum-likelihood parameter estimates and marginalization over many possible read alignments to achieve precision and recall of up to 99%. By pairing our high-confidence alignment strategy with long MinION reads, we resolved the copy number for a cancer-testis gene family (CT47) within an unresolved region of human chromosome Xq24.

Keywords

MinionNanopore sequencingComputer scienceComputational biologyDNA sequencerNanoporeBiologyGeneticsDNA sequencingDNANanotechnology

MeSH Terms

AlgorithmsGene DosageHigh-Throughput Nucleotide SequencingHumansNanoporesNeoplasms

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Publication Info

Year
2015
Type
article
Volume
12
Issue
4
Pages
351-356
Citations
674
Access
Closed

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Cite This

Miten Jain, Ian T. Fiddes, Karen H. Miga et al. (2015). Improved data analysis for the MinION nanopore sequencer. Nature Methods , 12 (4) , 351-356. https://doi.org/10.1038/nmeth.3290

Identifiers

DOI
10.1038/nmeth.3290
PMID
25686389
PMCID
PMC4907500

Data Quality

Data completeness: 90%