Literature DB >> 33532819

MultiNanopolish: Refined grouping method for reducing redundant calculations in nanopolish.

Kang Hu1, Neng Huang1, You Zou1, Xingyu Liao1, Jianxin Wang1.   

Abstract

MOTIVATION: Compared with the second generation sequencing technologies, the third generation sequencing technologies allows us to obtain longer reads (average ∼10kbps, maximum 900kbps), but brings a higher error rate (∼15% error rate). Nanopolish is a variant and methylation detection tool based on Hidden Markov Model (HMM), which uses Oxford Nanopore sequencing data for signal-level analysis. Nanopolish can greatly improve the accuracy of assembly, whereas it is limited by long running time since most executive parts of Nanopolish is a serial and computationally expensive process.
RESULTS: In this paper, we present an effective polishing tool, Multithreading Nanopolish (MultiNanopolish), which decomposes the whole process of iterative calculation in Nanopolish into small independent calculation tasks, making it possible to run this process in the parallel mode. Experimental results show that MultiNanopolish reduces running time by 50% with read-uncorrected assembler (Miniasm) and 20% with read-corrected assembler (Canu and Flye) based on 40 threads mode compared to the original Nanopolish. AVAILABILITY: MultiNanopolish is available at GitHub: https://github.com/BioinformaticsCSU/MultiNanopolish. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) (2021). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Year:  2021        PMID: 33532819     DOI: 10.1093/bioinformatics/btab078

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  3 in total

1.  Comparative evaluation of Nanopore polishing tools for microbial genome assembly and polishing strategies for downstream analysis.

Authors:  Jin Young Lee; Minyoung Kong; Jinjoo Oh; JinSoo Lim; Sung Hee Chung; Jung-Min Kim; Jae-Seok Kim; Ki-Hwan Kim; Jae-Chan Yoo; Woori Kwak
Journal:  Sci Rep       Date:  2021-10-20       Impact factor: 4.379

2.  Comparing Long-Read Assemblers to Explore the Potential of a Sustainable Low-Cost, Low-Infrastructure Approach to Sequence Antimicrobial Resistant Bacteria With Oxford Nanopore Sequencing.

Authors:  Ian Boostrom; Edward A R Portal; Owen B Spiller; Timothy R Walsh; Kirsty Sands
Journal:  Front Microbiol       Date:  2022-03-03       Impact factor: 5.640

Review 3.  Long-Reads-Based Metagenomics in Clinical Diagnosis With a Special Focus on Fungal Infections.

Authors:  Minh Thuy Vi Hoang; Laszlo Irinyi; Yiheng Hu; Benjamin Schwessinger; Wieland Meyer
Journal:  Front Microbiol       Date:  2022-01-06       Impact factor: 5.640

  3 in total

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