We now have PacBio sequencers, which can produce longer reads albeit with loads of errors. Will there come a time when a class of magical sequencers will be able to correctly read the genome end to end without error? If so, then lots of hot problems like assembly, read alignment etc. will die out. What all areas of bioinformatics will remain open for bioinformaticians who work on the algorithms/programming aspect of things then? Consequently, once you have this magical sequencer, what kinds of algorithmic questions will arise anew? Or, the emergence of such a sequencer will mean that only biologists will remain, and there will be no need of any bioinformatician?
2 answers
[31] (1) But as men at first made use of the instruments supplied by nature to accomplish very easy pieces of workmanship, laboriously and imperfectly, and then, when these were finished, wrought other things more difficult with less labour and greater perfection; and so gradually mounted from the simplest operations to the making of tools, and from the making of tools to the making of more complex tools, and fresh feats of workmanship, till they arrived at making, complicated mechanisms which they now possess. (31:2) So, in like manner, the intellect, by its native strength, [k], makes for itself intellectual instruments, whereby it acquires strength for performing other intellectual operations, [l], and from these operations again fresh instruments, or the power of pushing its investigations further, and thus gradually proceeds till it reaches the summit of wisdom.
Benedictus de Spinoza (1632–1677) - On the Improvement of the Understanding
I have my doubts that we are even close to the summit of wisdom in computational biology.
Spinoza FTW, excellent quote.
Such a technology would nicely remove a lot of the grunt work and leave us able to move on with the actual interesting part of the analysis :)
Such a technology would nicely remove a lot of the grunt work and leave us able to move on with the actual interesting part of the analysis :)
So only the biological inference making will remain. This means, that the role of a bioinformatician will become minimal if not eliminated altogether, assuming the bioinformatician is not a substitute for a biologist, right?
Umm, no, that's exactly what bioinformaticians are for. We're not going away, we just wouldn't be spending time doing alignments and assemblies. You know all those figures you see in papers involving complex integrative analyses? Those are done completely by bioinformaticians, since few "pure wetlab" biologists have the background needed to perform the analyses (and make the figures, but we're trying to teach them to do that).
Wait a few years .. let AI catch up :)
It is sometimes scary what google can figure out on based on what it knows about you and where you are at any given time if you use an android phone.
Luckily that likely won't happen before my remaining professional life comes to an end. I can hope, can't I?
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Actually, this type of sequencer already exists, as Oxford Nanopore sequencing on MinION and PromethION has no size limitation. The problem is just to keep the DNA intact while doing the library prep. The largest sequenced fragment (for now) is 510kb.
What about errors in these reads?
Depending on the chemistry used (1D vs 2D prep) the accuracy is currently respectively about 92% and 96%. So that's indeed not without errors and people working with Illumina will say that those are a lot of errors, but actually it's fine. If coverage is sufficient and with some polishing, you can get to ~99.9% accuracy.
Short answer, as nicely summarised by Devon is: OK, so now you have sequence, get on with the interesting stuff - analysis and interpretation.
It depends on the throughput of the magical sequencer. If it's low, then the only problems it solves are genome assembly/phasing and variant calling. Any question that's based on read counts (RNA-Seq, ChIP-Seq, etc) will remain.
And someone still has to analyze the data, so bioinformaticians will remain employable for the foreseeable future :-).