Literature DB >> 27559152

Characterization of MinION nanopore data for resequencing analyses.

Alberto Magi, Betti Giusti, Lorenzo Tattini.   

Abstract

The Oxford Nanopore Technologies MinION is a new device, based on nanopore sequencing that is able to generate reads of tens of kilobases in length with faster sequencing time with respect to other platforms. To evaluate the capability of nanopore data to be exploited for resequencing analyses we used the largest MinION data set to date and we compared with Illumina and Pacific Biosciences technologies. By using five different mapping approaches we estimated that the global sequencing error rate of MinION reads, mainly caused by inserted and deleted bases, is around 11%. The study of error distribution showed that substituted, inserted and deleted bases are not randomly distributed along the reads, but mainly occur in specific nucleotide patterns, generating a significant number of genomic loci that can be misclassified as false-positive variants. With 40× sequencing coverage, MinION data can produce at best around one false substitution and insertion every 10-50 kb, and one false deletion every 1000 bp, making use of this technology still challenging for small-sized variant discovery. We also analyzed depth of coverage distribution and we demonstrated that nanopore sequencing is a uniform process that generates sequences randomly and independently without classical sources of bias such as GC-content and mappability. Owing to these properties, the MinION data can be readily used to detect genomic regions involved in copy number variants with high accuracy, outperforming other state-of-the-art sequencing methods in terms of both sensitivity and specificity.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Keywords:  nanopore; resequencing; third generation sequencing

Mesh:

Substances:

Year:  2017        PMID: 27559152     DOI: 10.1093/bib/bbw077

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  23 in total

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Journal:  J Mol Diagn       Date:  2019-06-04       Impact factor: 5.568

2.  Direct sequencing of RNA with MinION Nanopore: detecting mutations based on associations.

Authors:  Noam Harel; Moran Meir; Uri Gophna; Adi Stern
Journal:  Nucleic Acids Res       Date:  2019-12-16       Impact factor: 16.971

3.  ACKR1 Alleles at 5.6 kb in a Well-Characterized Renewable US Food and Drug Administration (FDA) Reference Panel for Standardization of Blood Group Genotyping.

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Journal:  J Mol Diagn       Date:  2020-07-17       Impact factor: 5.568

4.  COSINE: non-seeding method for mapping long noisy sequences.

Authors:  Pegah Tootoonchi Afshar; Wing Hung Wong
Journal:  Nucleic Acids Res       Date:  2017-08-21       Impact factor: 16.971

5.  Long-read genotyping with SLANG (Simple Long-read loci Assembly of Nanopore data for Genotyping).

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Review 6.  Recombination in Positive-Strand RNA Viruses.

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Journal:  Front Microbiol       Date:  2022-05-18       Impact factor: 6.064

7.  Nano2NGS-Muta: a framework for converting nanopore sequencing data to NGS-liked sequencing data for hotspot mutation detection.

Authors:  Jidong Lang; Jiguo Sun; Zhi Yang; Lei He; Yu He; Yanmei Chen; Lei Huang; Ping Li; Jialin Li; Liu Qin
Journal:  NAR Genom Bioinform       Date:  2022-04-21

Review 8.  Approaches for characterizing and tracking hospital-associated multidrug-resistant bacteria.

Authors:  Kevin S Blake; JooHee Choi; Gautam Dantas
Journal:  Cell Mol Life Sci       Date:  2021-02-13       Impact factor: 9.261

9.  Randomly primed, strand-switching, MinION-based sequencing for the detection and characterization of cultured RNA viruses.

Authors:  Kelsey T Young; Kevin K Lahmers; Holly S Sellers; David E Stallknecht; Rebecca L Poulson; Jerry T Saliki; Stephen Mark Tompkins; Ian Padykula; Chris Siepker; Elizabeth W Howerth; Michelle Todd; James B Stanton
Journal:  J Vet Diagn Invest       Date:  2020-12-24       Impact factor: 1.279

10.  XCAVATOR: accurate detection and genotyping of copy number variants from second and third generation whole-genome sequencing experiments.

Authors:  Alberto Magi; Tommaso Pippucci; Carlo Sidore
Journal:  BMC Genomics       Date:  2017-09-21       Impact factor: 3.969

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