key: cord-0026491-cks6xacf
authors: Munro, Rory; Santos, Roberto; Payne, Alexander; Forey, Teri; Osei, Solomon; Holmes, Nadine; Loose, Matthew
title: minoTour, real-time monitoring and analysis for nanopore sequencers
date: 2021-11-15
journal: Bioinformatics
DOI: 10.1093/bioinformatics/btab780
sha: 9db7f3c61fb1e5088bfb2f49ec46989fc8a8a00d
doc_id: 26491
cord_uid: cks6xacf

SUMMARY: minoTour offers a Laboratory Informations Management System (LIMS) system for Oxford Nanopore Technology sequencers, with real-time metrics and analysis available permanently for review. Integration of unique real-time automated analysis can reduce the time required to answer biological questions, including mapping and classification of sequence while a run is in progress. Real-time sequence data require new methods of analysis which do not wait for the completion of a run and minoTour provides a framework to allow users to exploit these features. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are available at https://github.com/LooseLab/minotourcli and https://github.com/LooseLab/minotourapp. Docker images are available from https://hub.docker.com/r/adoni5/, and can be installed using a preconfigured docker-compose script at https://github.com/LooseLab/minotour-docker. An example server is available at http://137.44.59.170. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

High throughput real-time portable sequencing has transformed next generation sequencing from specialized centres to individual laboratories and previously unimaginable locations (Castro-Wallace et al., 2017; Quick et al., 2016) . Uniquely, Oxford Nanopore Technologies (ONT) sequencing enables true real-time analysis as sequence data are made available during, as well as after, a run (Loose et al., 2016; Payne et al., 2021) . Rapid analysis of data provides advantages where time to answer is important, such as pathogen genomics and clinical diagnosis of disease (Goes et al., 2019; Martignano et al., 2021; Quick et al., 2016; Sone et al., 2019) .

During a sequencing run, sequencing is controlled and tracked via ONT's MinKNOW software. MinKNOW can be used to remotely observe and monitor the progress of sequencing runs, view reports on metrics and recent historical run data. Numerous tools provide analysis of nanopore FASTQ data either during or after a run (Bruno et al., 2021; De Coster et al., 2018) . ONT also provides a cloud based service, epi2me (ONT, 2021), which enables various automated downstream analyses. However, as we show below, minoTour uniquely can capture both real-time sequence data and run metrics, can provide analysis and also acts as a comprehensive run archive. minoTour is open source and extensible, written using the Django framework, providing real-time insights into sequencer performance and sequence analysis. Visualized metrics allow users to see flow cell performance in real time. Built-in pipelines for alignment and metagenomics allow users to see experimental results in real time. Additional pipelines can easily be incorporated. For example, we can include a customized version of the ARTIC pipeline for SARS-CoV2 analysis described in more detail elsewhere (Munro et al., 2021) . minoTour also provides built-in adaptive sequencing (ReadFish only) (Payne et al., 2021) support in visualizations enabling users to monitor targeted sequencing in real time. Figure 1 illustrates the path data takes from the sequencer to the user. A single python tool, minFQ (https://github.com/LooseLab/mino tourcli), collects data from two sources. Firstly, run metrics are collected from MinKNOW via an ONT provided application programming interface (API). Secondly, base-called data are read either from user specified locations or found via the ONT API. These data are collected independently of each other, with only one needed to create the 

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Applications Note flowcell entry. They are sent to the minoTour server, which saves the sequencer metrics into the database, and stores the sequence data in Redis, a cache database. Celery performs asynchronous analysis of read data and can apply custom pipelines to perform analyses, ranging from base-called data summarizing to sequence alignment, metagenomics or custom workflows such as ARTIC (Munro et al., 2021; Tyson et al., 2020) . Read data are split into individual flow cells, which can be selected from a table to show all data held for individual runs using that flow cell ( Supplementary Fig. S1 ). These data can optionally be shared with other minoTour users if desired ( Supplementary Fig. S2 ). minoTour can also be configured to use twitter/email APIs and notify users about flow cell events such as disk shortages or reaching prespecified coverage thresholds for a reference genome ( Supplementary Figs S3 and S4 ). Reverse communication with the MinKNOW API allows users to send messages back into the MinKNOW logs for a permanent record such as notes on library reloading or comments on flow cell performance.

One of minoTour's strengths is its ability to automatically provide a historic record of runs ( Supplementary Fig. S1 ), and provide real-time key insights into ongoing runs (Supplementary Figs S5 and S6) . minoTour also provides a simple overview of all ongoing connected sequencers, quickly showing a user if any are under-performing, such as falling short on yield or speed, who can then respond accordingly ( Supplementary Fig. S7 ). minoTour can also remotely stop a run if required via the website. Using minoTour's minimap2 alignment pipeline for monitoring targeted or adaptive sequencing with ReadFish one can rapidly tell if coverage is accruing over specific targeted regions with sequenced and rejected reads able to be visualized separately (Supplementary Fig. S8 ). minoTour provides a simple metagenomics pipeline, using centrifuge (Kim et al., 2016) to visualize sample make-up, a breakdown of broad composition as well as more detailed investigation of select prechosen species by aligning reads classified in that taxa against one or more references (Supplementary Fig. S9 ). More complex pipelines such as the ARTIC pipeline can be incorporated ( Supplementary Fig. S10 ). We routinely use minoTour in the laboratory to monitor sequencing and use the available analyses to provide insights into sequencing experiments. The use of the Django framework enables other users to extend and develop minoTour at will. minFQ, once installed and activated, remains in the background uploading data to the minoTour server, automatically detecting new runs and sequence data ( Supplementary Fig. S11 ). Our implementation of minoTour with docker alongside detailed server installations for development leave the user with a variety of installation options. minoTour has been run on large centralized servers, or locally on laptops, enabling monitoring of sequencing runs for collaborative groups, sequencing facilities and individual users. At this time minoTour supports all platforms running flongle or minION flowcells. minoTour currently supports promethION for live data monitoring. Base-called data can be uploaded provided a suitably powerful server is running the app. Analysis pipelines will run, but will most likely fall behind the volumes of data that can be generated by a promethION.

BoardION: real-time monitoring of Oxford Nanopore sequencing instruments

Nanopore DNA sequencing and genome assembly on the International Space Station

NanoPack: visualizing and processing long-read sequencing data

Acute vector-borne viral infection: zika and MinION surveillance

Centrifuge: rapid and sensitive classification of metagenomic sequences

Real-time selective sequencing using nanopore technology

Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

Real-time monitoring and analysis of SARS-CoV-2 nanopore sequencing with minoTour. bioRxiv

ONT (2021) EPI2ME TM

Readfish enables targeted nanopore sequencing of gigabase-sized genomes

Real-time, portable genome sequencing for Ebola surveillance

Long-read sequencing identifies GGC repeat expansions in NOTCH2NLC associated with neuronal intranuclear inclusion disease

Improvements to the ARTIC multiplex PCR method for SARS-CoV-2 genome sequencing using nanopore

The authors thank Martin Blythe, Mike Stout and Sunir Malla for their input into this project. They also thank Claire Lonsdale for useful discussions and testing.

Work on minoTour was funded by the BBSRC [BB/M020061/1] as well as additional support from the Defence Science and Technology Laboratory [DSTLX-1000138444].

Conflict of Interest: M.L. was a member of the MinION access program and has received free flow cells and sequencing reagents in the past. M.L. has received reimbursement for travel, accommodation and conference fees to speak at events organized by Oxford Nanopore Technologies.