@article{
 title = {Improved data analysis for the MinION nanopore sequencer},
 type = {article},
 year = {2015},
 identifiers = {[object Object]},
 pages = {351-356},
 volume = {12},
 websites = {http://www.nature.com/doifinder/10.1038/nmeth.3290},
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 created = {2017-09-18T09:15:11.726Z},
 file_attached = {true},
 profile_id = {1c95d708-d42d-399e-b365-9d34fead1a19},
 last_modified = {2017-09-18T09:18:32.506Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
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 citation_key = {Jain2015},
 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.},
 bibtype = {article},
 author = {Jain, Miten and Fiddes, Ian T and Miga, Karen H and Olsen, Hugh E and Paten, Benedict and Akeson, Mark},
 journal = {Nature Methods},
 number = {4}
}

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