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Should Ion Torrent sequencing be used for
amplicon sequencing?
Lauren Bragg| Bioinformatician
13 February 2014
CSIRO COMPU...
What are ideal characteristics of an
amplicon-appropriate platform?
• Long read lengths
• High accuracy
• High throughput ...
The Ion Torrent PGM
Superficial comparison of Roche 454 Pyrosequencing and Ion Torrent
• Similar library preparation
• Lig...
I would not have recommended Ion Torrent
a year ago…
• High over-call/undercall error rate (~ 1.38% global mean rate)
InDe...
I would not have recommended Ion Torrent
a year ago…
• High over-call/undercall error rate (1.3%)
• Mean flow error-rate v...
I would not have recommended Ion Torrent
a year ago…
• High over-call/undercall error rate (1.3%)
• Mean flow error-rate v...
I would not have recommended Ion Torrent
a year ago…
• High over-call/undercall error rate (1.3%)
• Mean flow error-rate v...
But what about now?
Turns out it’s very difficult to analyse the new data using my existing
workflow…
• No longer support ...
After much ado, the results…

9 |
Flow error-rate

10 |
Flow error-rate profile differs between OOP
reads and non-OOP reads

11 |
High frequency indels
• Still present at around the same frequency (1 per 2Kb reference)

12 |
Summary and recommendations
Error-rate
• The over-call/under-call error-rate has decreased dramatically,
although flow-spe...
Acknowledgements
UQ

UWS

Gene Tyson
Margaret Butler
Phil Hugenholtz

Glenn Stone

Computational Informatics
Lauren Bragg
...
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Should Ion Torrent Sequencing Be Used For Amplicon Sequencing? - Lauren Bragg

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The Ion Torrent Sequencing platform now readily produces 400 base pair reads making it an appealing amplicon sequencing platform for ecognomics however, previous research indicates the reads tend to be of lower quality than alternative platforms. My presentation will help to put the strengths and limitations of the Ion Torrent PGM in perspective.

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  • Instead, supply unaligned BAM files with a flow-value fieldFlow-values in the BAM do not correspond exactly with the called sequenceIn fact – some ionograms are manipulated so much that they make insertion, deletion and substitution changes with very little evidence from the ionogram. Phase-correction step is responsible for generating called sequences which are out-of-phase (OOP) with the Ionogram.After contacting Life Tech, it would seem they won’t (suspect can’t) provide flow-values after phase-correction.
  • Transcript of "Should Ion Torrent Sequencing Be Used For Amplicon Sequencing? - Lauren Bragg"

    1. 1. Should Ion Torrent sequencing be used for amplicon sequencing? Lauren Bragg| Bioinformatician 13 February 2014 CSIRO COMPUTATIONAL INFORMATICS
    2. 2. What are ideal characteristics of an amplicon-appropriate platform? • Long read lengths • High accuracy • High throughput (or low cost per ‘tag’) • Amplicon composition an accurate reflection of the community composition 2 |
    3. 3. The Ion Torrent PGM Superficial comparison of Roche 454 Pyrosequencing and Ion Torrent • Similar library preparation • Light versus pH detections • ‘TACG’ flow pattern versus 32-base flow pattern • Both append 0+ bases during each flow Definitely a technology under development • Seems like the kits/chips/software are updated constantly • Length and density of reads makes it a compromise between 454 and Illumina •Paired-end is apparently available (Scott Chandry) 3 |
    4. 4. I would not have recommended Ion Torrent a year ago… • High over-call/undercall error rate (~ 1.38% global mean rate) InDel error-rate Substitution error-rate 4 |
    5. 5. I would not have recommended Ion Torrent a year ago… • High over-call/undercall error rate (1.3%) • Mean flow error-rate varies wildly between flow positions 5 |
    6. 6. I would not have recommended Ion Torrent a year ago… • High over-call/undercall error rate (1.3%) • Mean flow error-rate varies wildly between flow positions • High frequency indels (relative to reference) – 1 per 2Kb ref. genome Across both strands 6 | Strand-specific
    7. 7. I would not have recommended Ion Torrent a year ago… • High over-call/undercall error rate (1.3%) • Mean flow error-rate varies wildly between flow positions • High frequency indels (relative to reference) – 1 per 2Kb ref. genome • Small bias against low G+C%, and very strong bias against high G+C% bugs 7 |
    8. 8. But what about now? Turns out it’s very difficult to analyse the new data using my existing workflow… • No longer support SFF format • In theory the flow-values can be accessed from the flow-value field… • But it turns out that flow-values don’t correspond to the called sequence Flow cycle T A C G T Flow calls 0 1.15 0 3.32 0 Inferred A BaseCaller A GGG C GG • The phase-correction module can yield reads which are substantially different from their flowgram… (Out-of-Phase (OOP) reads). • Life tech won’t/can’t support a phase-corrected flowgram 8 |
    9. 9. After much ado, the results… 9 |
    10. 10. Flow error-rate 10 |
    11. 11. Flow error-rate profile differs between OOP reads and non-OOP reads 11 |
    12. 12. High frequency indels • Still present at around the same frequency (1 per 2Kb reference) 12 |
    13. 13. Summary and recommendations Error-rate • The over-call/under-call error-rate has decreased dramatically, although flow-specific error-rates persist. • Error profile differs between OOP and in-phase reads • High-frequency indels will still cause issues but unlikely to cause ‘genus’ changes in classification. Read-length • Read lengths consistently achieving 400bp Cheap cost-per-base • 3 million 400bp reads from a 316 chip for ~$900 (not including labour) Biases (TBA) 13 |
    14. 14. Acknowledgements UQ UWS Gene Tyson Margaret Butler Phil Hugenholtz Glenn Stone Computational Informatics Lauren Bragg Bioinformatician t +61 7 3214 2945 e lauren.bragg@csiro.au CSIRO COMPUTATIONAL INFORMATICS
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