Developments in next generation sequencing – June 2014 edition

This is the third edition of this visualisation, previous editions were in October 2013 and December 2012.

As before, full run throughput in gigabases (billion bases) is plotted against single-end read length for the different sequencing platforms, both on a log scale:

Developments in next generation sequencing June 2014














A new visualisation

Inspired by GapMinderWorld, a fascinating interactive visualisation of demographic data, and using their recommendations, I created an interactive ‘Motion Chart’ version of this visualisation on a Google spreadsheet. The chart allows to track the metrics throughout the years. Here is the final graph after running though all the data:


The X and Y axis are the same as for the first figure, the size of the data points are correlated with the number of reads per run.

You can explore the data interactively yourself by clicking on the graph.

Unfortunately, I didn’t find a way to change the default chart settings, so in order to have the best experience, make sure to adjust the chart as depicted below:



Note that the log scaling does not work as well as in the static picture at the top of this post. This is the reason I did not include the datapoint for Sanger sequencing. If someone can make this graph work in, say python, I’d be happy to include your results!

Notable changes from the October 2013 edition

  • I use numbers for the full run output. It was pointed out to me that this was not the case for the PacBio data, where I so far used the metrics for single SMRTCells (‘chips’) only. I have now chosen to report metrics for 12 SMRTCells as a full PacBio run, a compromise between the 8, 12 or 16 SMRTCells per run we have worked with
  • PacBio also upgraded to P5-C3 metrics
  • the Roche/454 GS Junior upgraded the read length to 700 bp (‘GS Junior+’)
  • the Illumina HiSeq2500 ‘1TB’ upgrade (2 × 125 bp read length and 4 billion reads per run)
  • I added the Illumina NextSeq 500 and HiSeq X (I chose the output for 1 instrument, even though one has to buy at least 10 of them)

Some comments

  • note how close together the data points fall for the GAII, HiSeq ‘Rapid Run’ mode and NextSeq 500.
  • as mentioned in the original blog post: some data was obtained by going to previous versions of company websites through the Internet Archive
  • I used full single-run specs with maximally stated throughput as available at the time of writing
  • sometimes, the total numbers of reads per full run and total bases obtained do not match up; for the figure, I always chose the reported throughput in bases
  • for Illumina, I chose to use the single-end read length, although the maximum throughput was based on the sum of all reads from a paired end run; I felt it unfair to double the read length for this platform for the figure
  • no changes for the 454 GS FLX+, Illumina GAII, HISeq ‘Rapid Run’ mode, SOLiD, Ion Torrent PGM and Proton
  • Oxford Nanopore’s MinION was not added as the instrument is not yet full commercially available – they are still in early access phase (MinION Access Program)

Data and figures are released under a CC0 license at figshare, with doi 10.6084/m9.figshare.100940. I’ve also added the content to Github at

As before: although I took utmost care in collecting the data, I may have gotten some of my numbers completely wrong, for which I apologise in advance; please help me correct any mistakes or omissions through leaving a comment, or sending me a pull request.

Finally, the raw data

Platform Instrument Year Reads per run Read length[1] Gigabases per run Source [2]
ABI Sanger 3730xl ND 96 800 0.0000768
454 GS20 2005 200000 100 0.02
454 GS FLX 2007 400000 250 0.1
454 GS FLX Titanium 2009 1000000 500 0.45
454 GS FLX+ 2011 1000000 700 0.7 1
454 GS Junior 2010 100000 400 0.04 2
454 GS Junior+ 2014 100000 700 0.07 16
IonTorrent PGM 314 chip 2011 100000 100 0.01 3
IonTorrent PGM 316 chip 2011 1000000 100 0.1 3
IonTorrent PGM 318 chip 2011 5000000 100 0.5 3
IonTorrent PGM 318 chip 2012 5000000 200 1 3
IonTorrent PGM 318 chip V2 2013 5000000 400 2 12
IonTorrent Proton PI 2012 50000000 200 10 4
Illumina GA (launch?) 2006 28000000 25 0.7
Illumina GA 2008 28000000 35 1 5
Illumina GA II ND 100000000 50 5
Illumina GAIIx 2009 440000000 75 33 6
Illumina GAIIx 2011 640000000 75 48 7
Illumina GAIIx 2012 640000000 150 95 8
Illumina HiSeq 2000 2010 2000000000 100 200 9
Illumina HiSeq 2000 2011 3000000000 100 600 10
Illumina HiSeq 2000/2500 2014 4000000000 125 1000 17
Illumina HiSeq 2500 RR 2012 600000000 150 180 13
Illumina HiSeq X 2014 6000000000 150 1800 18
Illumina NextSeq 500 2014 400000000 150 120 14
Illumina MiSeq 2011 30000000 150 4.5
Illumina MiSeq 2012 30000000 250 8.5 11
Illumina MiSeq 2013 30000000 300 15 14
SOLiD 1 2007 40000000 25 1
SOLiD 2 2008 115000000 35 4
SOLiD 3 2009 320000000 50 16
SOLiD 4 2010 2000000000 50 100
SOLiD 5500xl 2011 3000000000 60 180
SOLiD 5500xl W 2013 3000000000 75 320
PacBio RS C1 2011 36000 1300 0.540
PacBio RS C2 2012 36000 2500 1.080
PacBio RS C2 XL 2012 36000 4300 1.858
PacBio RS II C2 XL 2013 47000 4600 2.594 15
PacBio RS II P5 C3 2014 44000 8500 4.500 15

[1] mode or average
[2] Sources: see this file from the github repo.

16 thoughts on “Developments in next generation sequencing – June 2014 edition

  1. Hi Lex,

    thank you for the nice graph! I will include it in my thesis.

    Also the DOI hyperlink in the “Availability” section is incorrect.



    • Thanks for confirming the launch year. Technically you are correct that in 2006 the company name should be Solexa. This will be addressed in the next edition. Thanks!

  2. Too bad you used the worst of the Sanger instruments for your comparison, but the difference is still stark.

    The Amersham/GE Healthcare MegaBACE 4500 was a 384-capillary instrument, with readlengths over 1000 bp. Yet, due to ABI’s better dominance in the market, the MB 4500 never had much penetration.

    Disclosure: I developed the MegaBACE 4500.

    • Hmm, you’re giving me a dilemma: yes, I could add other then-available instruments, which would be nothing else than fair. however, I have no overview of which these were, when they were available, and what the relevant metrics were. Or, if I don’t, I should remove the ABI… I’ll give this a bit of thought. Oh, and when I just started working here in 2005, we still had a MegaBACE – although I never used it.

  3. Hi, could I use one of your illustration in my master thesis? i would indicate the source obviously..
    thanks in advance

  4. Hi. Excellent summary which I have shared around my institution. As a PGM evangelist can I point out that 314v2 and 316v2 chips were launched a while back enabling 400bp reads on those chips. Also I presume you’re comparing on an “even” grounding and using the official manufacturer’s numbers? I only mention as I would be pretty disappointed with a 314v2 run that didn’t come out with >250,000 reads and 316v2 that didn’t come to >3m

    • Thanks! My bad for not following along. Was this release in 2014 or 2013? I need to update the graph (HiSeq4000! RapidRun v2! pacBio P6-C4!) so then I will add your suggested updates.

      • I only now see you are talking about the v2 for the 314 and 316 chips. I decided to take the maximum output chip for the PGM, i.e.the 318, to not clutter the graph with too many data points and lines for this instrument.

  5. Dear Lex,
    Just one more historical update to your’s table
    The ABI 3730/3730XL was released in summer 2002 to commercial users (see this link):
    Before it there was ABI 3700 96cap (released in 1998), which had a bit shorter read length (Q20 was arround ~550bp or so), but it depended on array lenght (50cm) run voltage/time, polymer used, etc:

    • Thank you! Such information is not easy to find (I’m still uncertain about release dates for SOLiD…). I will try to incorporate this information for the next release (it’s about time for an update, really…)

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