MinION (Oxford Nanopore)

Introduction

Entirely unique sequencing method, where the flowcell is inserted into a USB container, and from there, plugged into a computer.

Due to its small size in comparison with Illumina, IonTorrent and PacBio, this sequencing tool is eminently suited to field work.

Overview

Reputed advantages

• flowcell pores good for several runs, until they die out, which they may do at different times.
• Reads an be quite long ... 100kb is possible.

Shortcomings

• Computer, usually a laptop, needs to be continually connected to internet, and to be in high workload mode (no economy nor sleep mode allowed).
• accuracy at least an order of magnitude worse than Illumina (~90% vs >99%)
• Probably more expensive than Illumina on a per-base basis, although there is no service contract involved as one might expect from Illumina. Low cost of Illumina cost is largely down to economies of scale.

Characteristics

• 1D, which means single-strand reading, is the most common and mature of MinION's modes.
• 2D, where both strands are read, one after the other, is possible, and allows much better accuracy, but is more demanding and more prone to errors.

Software Round-up

The software required can be split into two groups of programs:

• Sequencing generation
  • MinKNOW, for control of MinION device & run parameters
  • Metrichor, for cloud basecalling of event data
  • Chronolapse a screen image grabber for record keeping
  • TeamViewer, for remote control of MinION computer
  • MinoTour, live monitoring / control of run while sequencing (a collaboration with Matt Loose of Nottingham University).

• Sequence File Analysis
  • Poretools, poRe Sequence extraction and data summaries (deevloped by Nick Loman and Aaron Quinlan (latter of bedtools fame)).

Developments during 2016

At the beginning of 2016, udring a regular run, MinION could:

• Process 500Mb of DNA from a flow-cell
• Each pore could read 70 bases/second
• Accuracy still low at 70-80%

Major steps were made to improve this:

• Pore technology moved from R7 (had patent conflict problems with Illumina) to R9 (better throughput, higher accuracy)
• implemented new deep-learning algorithm
• closer collaboration with key academic researchers.

Links

• Brian Naugton's blog entry 11 Oct 2016 taking stock of recent advances
• Nature paper 11 Feb 2016 describing Minion use in Ebola outbreak