Nanopore tools development
Developing tools for in-field classification of environmental samples.
Oxford Nanopore Technologies' (ONT) MinION, introduced in 2014, is an exciting new compact, low-cost sequencing technology that offers long reads (thousands of bases of DNA) and a streamed mode of operation enabling analysis of data as it is generated. These attributes make it ideally suited to in-field use. However, part of the process of generating sequencing data involves converting an electrical signal from the DNA sensing pore into a sequence of bases and this is performed via an internet basecalling service.
For in-field deployment, this is unsatisfactory, as we cannot rely on high speed, reliable data connections. In this project, we seek to address this constraint by developing local, low-power algorithms and tools for classification of environmental samples which can be deployed in-field without an internet connection.
Initial work by EI on Nanopore tools resulted in the publication of NanoOK (Leggett et al. 2015, Bioinformatics), a comprehensive tool for understanding data quality and error profiles of MinION sequence data. This was subsequently used for some of the analysis from the MinION Analysis and Reference Consortium’s initial paper (Ip et al. 2015, F1000Research).
In this latest work, we aim to develop a tool for reliable and accurate in-field classification of environmental samples sequenced on the MinION.
NanOK - Multi-reference Alignment Analysis
Flexible, multi-reference software for pre- and post-alignment analysis of nanopore sequencing data, quality and error profiles
NanoOK (pronounced na-nook) is a tool from EI for alignment and analysis of Nanopore reads. NanoOK will extract reads as FASTA or FASTQ files, align them (with a choice of alignment tools), then generate a comprehensive multi-page PDF report containing yield, accuracy and quality analysis.
NanoOK has a number of dependencies - Perl, LaTeX, R and an alignment tool - which means it works best on Linux and Mac OS platforms.
Dstl (Defence Science and Technology Lab)
We see this work as having a wide variety of application areas, with our initial focus being on the detection of plant and animal pathogens. Early detection and reliable classification of these organisms can be an important step in understanding and preventing the spread of disease. The algorithms and tools developed as part of this project will be released as open source software, enabling the community to take and apply to a wide range of new applications.
Nanopore tools help researchers analyse in-field sequencing data. Credit: Shutterstock / Quick Shot