I had guessed that January's drop was connected to Illumina's announcement in the same month, so was surprised that it reversed in April.
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My guess (and it's really just a guess) is that they are ignoring the X Ten in figuring the prices. Illumina has been raising prices on their sequencing kits every April 1st, so that little bump makes sense. However, I'm not sure that they're taking into account the release of the v4 chemistry for the HiSeq 2500. That reduced the list price for 1Gb of sequence from $43 down to $29. (For comparison, it's just $7/Gb for the HiSeq X.)Originally posted by xyzzy123 View PostI had guessed that January's drop was connected to Illumina's announcement in the same month, so was surprised that it reversed in April.
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https://www.genome.gov/sequencingcosts/ is no longer being updated. It looks like they hit the end of the graph and don't want to extend it. In any case, since the price is now dropping much more _slowly_ than Moore's Law, in another 10 years or so at this rate Moore's Law will catch up and the graph would look kind of silly.
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Indeed. Those costs are misleading. There should be all sorts of asterisks detailing the assumptions. Might as well throw in the higher per-base cost of using PacBio to complete a genome.Originally posted by Brian Bushnell View PostDue to all the artificial limitations on the X10, I don't consider it an accurate reflection of real sequencing costs.
I've always hated that graph because of the misapplication of "Moore's Law". Stupid. But I have seen it in so many presentations that I just grit my teeth.
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by GATTACATLove this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
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07-01-2026, 11:43 AM -
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by SEQadmin2
I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...-
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