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Title: Systematic and stochastic influences on the performance of the MinION nanopore sequencer across a range of nucleotide bias

Abstract

Emerging sequencing technologies are allowing us to characterize environmental, clinical and laboratory samples with increasing speed and detail, including real-time analysis and interpretation of data. One example of this is being able to rapidly and accurately detect a wide range of pathogenic organisms, both in the clinic and the field. Genomes can have radically different GC content however, such that accurate sequence analysis can be challenging depending upon the technology used. Here, we have characterized the performance of the Oxford MinION nanopore sequencer for detection and evaluation of organisms with a range of genomic nucleotide bias. We have diagnosed the quality of base-calling across individual reads and discovered that the position within the read affects base-calling and quality scores. Finally, we have evaluated the performance of the current state-of-the-art neural network-based MinION basecaller, characterizing its behavior with respect to systemic errors as well as context- and sequence-specific errors. Overall, we present a detailed characterization the capabilities of the MinION in terms of generating high-accuracy sequence data from genomes with a wide range of nucleotide content. This study provides a framework for designing the appropriate experiments that are the likely to lead to accurate and rapid field-forward diagnostics.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1430904
Report Number(s):
SAND-2018-0811J
Journal ID: ISSN 2045-2322; 661556
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 8; Journal Issue: 1; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Krishnakumar, Raga, Sinha, Anupama, Bird, Sara W., Jayamohan, Harikrishnan, Edwards, Harrison S., Schoeniger, Joseph S., Patel, Kamlesh D., Branda, Steven S., and Bartsch, Michael S. Systematic and stochastic influences on the performance of the MinION nanopore sequencer across a range of nucleotide bias. United States: N. p., 2018. Web. doi:10.1038/s41598-018-21484-w.
Krishnakumar, Raga, Sinha, Anupama, Bird, Sara W., Jayamohan, Harikrishnan, Edwards, Harrison S., Schoeniger, Joseph S., Patel, Kamlesh D., Branda, Steven S., & Bartsch, Michael S. Systematic and stochastic influences on the performance of the MinION nanopore sequencer across a range of nucleotide bias. United States. doi:10.1038/s41598-018-21484-w.
Krishnakumar, Raga, Sinha, Anupama, Bird, Sara W., Jayamohan, Harikrishnan, Edwards, Harrison S., Schoeniger, Joseph S., Patel, Kamlesh D., Branda, Steven S., and Bartsch, Michael S. Fri . "Systematic and stochastic influences on the performance of the MinION nanopore sequencer across a range of nucleotide bias". United States. doi:10.1038/s41598-018-21484-w. https://www.osti.gov/servlets/purl/1430904.
@article{osti_1430904,
title = {Systematic and stochastic influences on the performance of the MinION nanopore sequencer across a range of nucleotide bias},
author = {Krishnakumar, Raga and Sinha, Anupama and Bird, Sara W. and Jayamohan, Harikrishnan and Edwards, Harrison S. and Schoeniger, Joseph S. and Patel, Kamlesh D. and Branda, Steven S. and Bartsch, Michael S.},
abstractNote = {Emerging sequencing technologies are allowing us to characterize environmental, clinical and laboratory samples with increasing speed and detail, including real-time analysis and interpretation of data. One example of this is being able to rapidly and accurately detect a wide range of pathogenic organisms, both in the clinic and the field. Genomes can have radically different GC content however, such that accurate sequence analysis can be challenging depending upon the technology used. Here, we have characterized the performance of the Oxford MinION nanopore sequencer for detection and evaluation of organisms with a range of genomic nucleotide bias. We have diagnosed the quality of base-calling across individual reads and discovered that the position within the read affects base-calling and quality scores. Finally, we have evaluated the performance of the current state-of-the-art neural network-based MinION basecaller, characterizing its behavior with respect to systemic errors as well as context- and sequence-specific errors. Overall, we present a detailed characterization the capabilities of the MinION in terms of generating high-accuracy sequence data from genomes with a wide range of nucleotide content. This study provides a framework for designing the appropriate experiments that are the likely to lead to accurate and rapid field-forward diagnostics.},
doi = {10.1038/s41598-018-21484-w},
journal = {Scientific Reports},
number = 1,
volume = 8,
place = {United States},
year = {2018},
month = {2}
}

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