ONT Updates: GridION X5, PromethION, 1D^2, Scrappie, FPGAs and More

Clive Brown gave a webcast today with updates on a number of Oxford Nanopore topics, but clearly the flagship announcement was a new instrument, GridION X5.  Due to the raging snowstorm in the Boston area I was home with my teammate and we've been doggedly going through the tweets (now storified) and my notes (plus David Eccles' nice set) to retrieve the juiciest bones therein.

Blog team member intently watching @Clive_G_Brown webcast - now must confer & write-up impressions pic.twitter.com/jPGpw1w0lg

— Keith Robison (@OmicsOmicsBlog) March 14, 2017

GridION X5 

GridION X5 is intended to serve labs that see the MinION as too small but the PromethION as overkill (more on the big beast later in this post).  Sporting five flowcells and hefty on-board compute, it is intended to replace the snarl of cables and machines seen in larger MinION labs.  GridION is planned to launch on May 15th, just after the London Calling confab. Clive swears that manufacturing is well underway and that this design can be produced in bulk.

GridION X5 and PromethION licenses will both permit use in a service capacity; it will now be legitimate to profit from sequencing other people's samples.  Clive didn't elaborate on the logic of blocking MinION users from this, saying only he and Spike (Wilcocks, the ONT commercial point person) understood the logic.  I'll agree I don't, but presumably it is more of an internal commercial decision than anything anyone on the outside would cook up.  In any case, Oxford will also be launching a certified service provider program.

Clive didn't dwell on operational details, as it was late in the presentation slot by this time (I've reported this presentation according to my own peculiar order, not the temporal one).  Presumably the five flowcells are fully independent.  These are MinION-class flowcells but apparently not interchangeable, creating inventory headaches for labs running both since the flowcells definitely have a shelf life.  [Lars G T Jorgensen found that the ONT website does say they are MinION flowcells; the slides said "Based on current MinION flow cell design" which I took to be a new variant 2017-03-15 15:53] The on-board compute capacity should be sufficient to keep up with basecalling.
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GridION X5 is a huge step up in cost over the MinION.  There are two pricing schemes, one treating the instrument as a capital item and pricing flowcells more cheaply and another "reagent rental" pricing scheme.  The upfront option costs $125K but then you can buy up to 450 flowcells over the next 18 months for $299 each.  The reagent rental option opens with only a $15K training fee (included in the purchase option) upfront, but requires a commitment to 300 flowcells at $450 each.

I've plotted out the cost curves (below) for these and am scratching my head; the purchase option (blue triangles) is only better for 100 or fewer flowcells than the reagent rental (red circles).  I'm wondering if someone at ONT didn't quite do their sums correctly -- or perhaps I haven't?  I would have at least thought the flowcell discount would disappear with at least breakeven versus the reagent rental pricing, but you can see from the jump in the curve this isn't true.

Ideally I'd have a curve for MinION there, but I don't know the cost for the equivalent of the compute included in the instrument. It's a nice box - "latest gen CPU", custom FPGA (more on those in a bit), 64Gb RAM and 8 TB SSD, but $125K seems high.  The lowest MinION flowcell cost is $500, so the slope would be steeper.  If you want to run as a service to external customers, or just like a neater look than some 3D-printed MinION holder and cables to your compute, then GridION X5 might be worth it.

PromethION

Clive described PromethION as the elephant in the room, as the PEAP (PromethION Early Access Program) has been far behind schedule.  This prompted me to write a very skeptical piece late last year, wondering if PromethION had been a mistaken detour.  Clive promised that somewhere between 12 and 20 of the PEAP sites would receive four flowcells which will ship on April 3rd.  Clive noted that PEAP users have been very patient, with perhaps just one customer requesting refund of their deposit.

In addition to kits going out, PromethION will be undergoing a complete makeover.  Oxford's engineers decided that cramming all of the compute inside the sequencing box just wasn't working out, so a computing unit in tower configuration will be coming out.  With FPGA coprocessors, this beast will have up to 80 teraflops of power, which Clive believes will enable real time basecalling even when the machines are fully configured to 48 flowcells and the pores run at 1000 bases per second.  ONT is also planning to implement their Epi2Me software in this system, so that users averse to cloud computing can run all their workflows on spare capacity within the tower unit.

After  tower launches (scheduled for Q3), then PromethION will slim down, as the lower section will contain only a networking switch.  This would enable connecting to the tower unit, as well as to local compute power.  Around Q4, Oxford expects to enable PromethIONs to run all 48 flowcells; the slimmer case would probably launch around the same time.  Eventually, early next year, the entire box will be re-engineered to accomodate all that is learned during PEAP.  That future product is already designated PromethION MkI.

On the manufacturing front, Clive stated the backlog of PromethION orders should be cleared by Q3 of this year, though he lamented he had stated a year ago that this milestone was to be reached in Q3 of 2016.  Flowcell manufacturing is scaling up as well, as seen in the tweeted image below

CB: PromethION early instruments continue to ship, flow cell production underway #nanoporeconf pic.twitter.com/xPQOQLRb7B

— Oxford Nanopore (@nanopore) March 14, 2017

Throughput

Clive threw around a lot of throughput numbers for all the instruments, but perhaps more interesting is that Oxford is now putting a team on the discrepancy between yields obtained internally and those seen in the field, which are at least 2X and perhaps much worse (in particular, I seem to emit some sort of MinION dampening field).  Oxford's belief is that low yields are largely due to users starting with contaminated, sheared or poorly quantitated DNA.  So ONT will be exploring the limits of these problems to nail down their effect sizes.

Longer flowcell lifes are on the horizon; Clive has tweeted out results of 60 hour runs. Long-lived pores need good libraries though.

ONT recently increased yields by improving the solution to pore jamming.  A new release of MinKNOW will shorten the detction time for blocks to under 2.5 seconds; currently this is around 5 seconds.  A bullet suggests that better QC tools integrated into MinKNOW are coming, an idea I suggested earlier this year. ONT's Dan Turner announced today a new command line tool called 'wub' which will apparently provide QC metrics on runs.

1D^2 Chemistry

Clive announced that 2D library prep kits will be discontinued on May 5th. While he made no mention of it, the 2D discontinuation seemingly ends the point of dispute in Pacific Bioscience's intellectual property actions against ONT.  Instead, the new 1D^2 chemistry will be rolled out along with a slight change to the pore, R9.5.  R9.5 chemistry is promised to be fully backwards compatible with all R9.4 callers and kits. 1D^2 has not physical linkage between the two strands.  Instead, as the first strand is pulled through it tends to drag the 5' end of the second strand towards the pore (illustration below).  With R.9, about 1% of the strands show the 1D^2 phenomenon, in which the second strand is acquired by the pore almost immediately after releasing the first strand.  I've seen a few "mirror reads" in our data, in which the software does not recognize the brief free pore state and treats both as one long read.  The R9.5 pore increases the 1D^2 phenomenon to around 60% of reads, and Clive leans towards the explanation that nicks or failure to ligate an adapter are significant contributors to the 40% of reads which do not exhibit the effect.

The real beauty of 1D^2 is that the 2D chemistry caused problems; many complement strands had notably lower accuracy than the template strand.  This has been blamed on effects of the hairpin which tied the two ends together.  With 1D^2, no such degradation of signal is seen.  With the current basecallers, modal error rates around 5% are reported by ONT for 1D^2; with the newer Scrappie basecaller Clive thinks this may drop to close to 1%.

Holders of developers' licenses will have access on the 27th of this month to custom flowcells with the R9.5 chemistry and the prototype 1D^2 basecaller, with community release of 1D^2 at the London Calling meeting in early May.  Longer lived flowcells based on the R9.5 chemistry will apparently ship on April 24th, a bit before 1D^2 is available.  Clive suggested that kits may be available which lack the 1D^2 capability, for users with applications in which total independent sequence is more important than the higher accuracy.  Side thought: since 1D^2 happens at a low level in any case, it will still be useful for the basecallers to recognize this so that the non-independence of the reads is recognized and so that the monster pseudo-hairpins I've seen are resolved into 1D^2 reads.

Basecalling 

The long-hinted axe on cloud basecalling drops on March 21st. Clive noted that the cloud basecalling was very useful for developing the basecalling software, but once local basecalling was made available it was left in place as a safety net.  That net is going away; Clive remarked that if you leave a safety net in place "people start using it as a hammock".  Oxford will be releasing new compute specs shortly; with computers from this list it should be nearly possible to run local basecalling in sync with sequence generation.  A new tool called Lamprey will allow users to effectively mimic the cloud basecalling system on their local cluster.

Clive presented some error numbers based on a 20X coverage assembly of E.coli.  The first slide below shows the consensus error profile for this assembly using the current basecaller and either 1D or 1D^2 chemistry.  Curiously, the 1D^2 actually does worse on mismatch and insertion (!), but improves on deletions in both homopolymer and non-homopolymer cases by 2X-3X

The yet unreleased Scrappie basecaller relies on a "transducer" model.  Rather than being released separately, this will apparently be rolled into production basecallers on April 20th.  The data provided for Scrappie on the E.coli assembly is only for the 1D chemistry, but it improves mismatches by a factor of 4, non-homopolymer deletions by a factor of 13 (!!), homopolymer deletions by a factor of 4 and a very small (~6%) improvement on insertions.

ONT had remarked before that Pacific Biosciences had pointed out ONT's homopolymer issue in a presentation, showing a case in which a polymorphism has been implicated (well, Clive disputed this) in Alzheimers.  With newer chemistry and basecallers, a heterozygous sample is correctly called from the consensus. Note also the belated appearance of Monty Python references; both prior webcasts had them in the titles!

A huge upcoming change in the basecallers is the elimination of the "event" model, and in many cases elimination of the FAST5 files altogether.  The current software parse the raw electrical signal into discrete events which are stored in the FAST5.  Clive has apparently wanted to ditch the events for some time, as he has long felt it was a poor model.  With the newer basecallers, the option to generate FASTQ or unaligned SAM will be available, or users will be able to get FAST5 files which have just raw signal -- and are promised to be over 80% smaller.  Developer releases Scrappie with the new scheme will occur during Easter.

FPGA Basecalling Accelerator

Clive has previously broached the idea of a Field Programmable Gate Array (FPGA) approach to accelerating basecalling.  Working in collaboration with Intel, Oxford is continuing to work towards a PCIe FPGA card which could go into PCs, as well as a USB device to support MinION on laptops.  The USB device is farther out and ONT is not yet sure if it will be inline with the MinION or occupy a second port.  As shown below, basecalling speeds of 50Kbases/s are achievable with a desktop CPU hitting 0.5 teraflops, but only 10% of that power is actually used.  As Clive explains it, the recurrent neural networks now being used for basecalling are challenging to parallelize, as information must feed back-and-forth through the network.  With an FPGA it is possible to achieve 60% utilization of a 10 teraflop rated device and hit 7.5Mbases/s calling with the same power draw as the desktop CPU. PromethION is slated to deliver about 65Mb/s, so a set of 10 such FPGAs should be able to keep up.  Clive also stressed that FPGAs can be scaled up-and-down; the solution for SmidgION and Flongle can use a smaller circuit, for MinION a bit bigger and for PromethION a really large one.

Quick Flashes and No Updates

Clive gave a number of small updates, a few things showed up only in his release schedule slide and others got a single sentence.  Many other items were simply mentioned as exciting but no updates until London Calling. I will bang out most of these as 1-2 sentences

Clive is planning a third go at the CliveOme, this time using megaread protocols.  He is holding out hope of getting a centromere-spanning read or even an entire chromosome.  ONT has an effort to extend leviathan reads to entire chromosomes (I think yeast was mentioned).

Approximately 4000 MinIONs have been shipped!

VolTRAX chemistry should ship on March 27th. VolTRAX multiplexing planned release on May 15th.

Direct RNA early access is listed as March 20th; a bit of a puzzler since there have been tweets of direct RNA results.  But perhaps those were just 1st trials and this represents a reliable supply.

Essentially no news until London Calling: cDNA (though Clive said it is spectacular), sequencing from 20 pg input via whole genome amplification, barcoding kits (I'm hoping Oxford goes beyond 12 barcodes; that's only a good start!), Zumbador, Flongle, SmidgION and Metrichor/Epi2Me.


Okay, that's all.  Hoping my accuracy is better than my sometimes garbled reporting on leviathan reads!  Can't wait for London Calling!

[Jared Simpson found I wrote $399 instead of $299 for the flowcell price in the upfront GridION X5 pricing scheme; my graph generator had the correct number but now the text is fixed 2017-03-14 23:41]
[Vinzenze Lange pointed out the original cost curve plot was off; I botched the change in slope after the flowcell discount runs out 2017-03-15 06:32]
[Vinzenze Lange pointed out my text reversed "red" and "blue" -fixed 2017-03-15 10:47]


Should have put this in originally - Python code for the plot

import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt

own=125000;
rentCost = []
ownCost = []
fcN  = range(0,600,10)

rentBase=14999;
ownBase=125000

for fc in fcN:
    if fc<=450:
       ownCost.append(ownBase+299*fc)
    else:
       ownCost.append(ownBase+299*450+(fc-450)*475)

    if fc>300:
       rentCost.append(rentBase+475*fc)
    else:
       rentCost.append(rentBase+475*300)

rentPlot=plt.plot(fcN,rentCost,'ro',label="Rent")
ownPlot=plt.plot(fcN,ownCost,'b^',label="Own")
plt.ylabel("Total $")
plt.xlabel("Flowcells")
plt.ylim(0,350000)
#plt.legend(handles=[rentPlot,ownPlot])

of = open("/home/krobison/www/plots/test.png","w")
plt.savefig(of,format="png")