So I see some are already discussing Jeanson’s work. And it seems scientists are emotionally invested, as well as intellectually invested
But I’m curious how many who understand the science think this conclusion is just flat out wrong or “just right” when looking at the same data? Or we just need more studies? I’m not scientist: I cannot evaluate it based on science.
“Conversely, our results also strongly challenge the evolutionary timescale (fig. 2). Rather than confirm a history for humanity that stretches back hundreds of thousands of years, these results reject this hypothesis. If men have been around for hundreds of thousands of years, they should have accumulated mutations 8- to 59-times the amount currently observed. Instead, we observe only a few thousand years’ worth of mutation accumulation.”
There is a lot I like about Jeanson’s work. He is correct that YEC and evolutionary models require totally different mutation rates. He predicts that mutation rates are far higher (about 50x higher) than evolutionary science would predict. That is a major point of agreement and common ground. It seems we all agree with him on this.
The issue, however, is that he hasn’t quite realized that the measured rates of mutation are closely aligned with evolutionary science, and about 50x lower rate than the YEC model predicts. It is really just that simple.
How is he confused about this? It is hard to know for sure. He is a smart guy, but he goes through a lot of gymnastics and convolution to claim that the measured rate is something different than what we observe all the time. He does not deal with the rates that other scientists compute from the data. And the data on human mutation rates is growing and stronger all the time. Scientists are going to keep sequencing human genomes and measuring this rate with higher and higher accuracy, with better and better methods. So his whole argument rests on extremely thin ice…
Starting from the assumption of common descent, we can look at the amount of differences between humans/chimp DNA to predict a mutation rate, the evolution-mutation-rate.
Starting from the assumption of YEC, we can look at the amount of differences between human DNA from different people to predict a mutation rate, the YEC-mutation-rate.
YEC-mutation-rate is about 50 times larger than evolution-mutation-rate.
Then we can go and directly measure the mutation rate in humans today. We do this by sequencing the genomes of couples and their children, removing sequencing errors, and counting up how many times there is a mutation in a single generation. This is the observed-mutation-rate.
We observe there is about 50 single nucleotide mutations per generation, across six billion nucleotides of DNA, which is almost spot on the evolution-mutation-rate (a bit too low, not too high). To support the YEC-mutation rate, in contrast, we would need to see 5000 to 10000 point mutations per generation. That is just far more than we actually observe.
So Nathanial’s basic approach is reasonable. It is just on the last part, looking at the observed mutation rate, that he stumbles.
OK - as I read through, he’s arguing that the raw data is buried for the two higher quality studies and he looked at it. Are you saying based on HIS own observations on the raw data presented in his paper, his “observed-mutation-rate” applied to human history, he’s still wrong?
Or his observed-mutation rate is just bad science?
Or there’s no difference from what he’s saying from evolutionary theory and he’s just confused?
First, those are not higher quality studies, but have very high error rates.
Second, he “forgets” to subtract out the error when he computes the rates, which is what gives him the higher mutation rate (which is erroneous).
Third, this is just 0.005% of the genome (mtDNA) or 1.8% (Y-Chromosome). We have higher quality studies on the entirely genome that show him wrong, and he just ignores this.
Yes, we would call this bad science.
His characterization of evolutionary theory and the way he computes the evolution-mutation-rate is confused. However, it doesn’t really matter much, because we agree on this:
Rather than quibble with him on the details of how he computes the evolution-mutation-rate, I’m happy to take this as common ground. Where things fall apart is the actual data. It could have demonstrated him correct. It could have disproven evolution. It could have disproven both evolution and YEC. Instead, it was consistent with evolution, and inconsistent with YEC.
Of note, they compared the observed mutation rate to that predicted by evolution, and found that the observed mutation rate alone was not correlated (by region) as well as they hoped to the rate predicted by common descent (see red arrow). However, when they added in the effect of recombination (see yellow arrow) the observed mutation (by region) was in fact exactly what the evolutionary model predicts (blue curve).
What wasn’t even on the table? There doesn’t seem to be any way to construe these results as 50 times more than what evolution allows. This is also across 99.995% of the genome (excluding mt-DNA), so it includes Y-Chromosomes. It is far higher quality data than Nathanial relies upon, and it has been confirmed by several follow up studies.
So, he is lying when he says there are only two studies?
“To date, two published studies explicitly attempt to obtain the pedigree-based per-generation mutation rate for the Y chromosome (Helgason et al. 2015; Xue et al. 2009). Both studies have reported results to be consistent with the evolutionary timescale.”
I would not call this lying. He is writing about a topic way outside his expertise and may not realize how wrong he is. I would say that this is a totally false claim, whether Nathaniel realizes it or not.
As it is, you can see for yourself though, he does not meantion this study (and many others like it):
I do think it is interesting that he acknowledges that “Both studies have reported results to be consistent with the evolutionary timescale.” However, as I already explained, the way he computes the mutation rates is not valid.
Is this lying? Is it incompetence? Is it loyalty to the AIG belief statement? Something else or some mix of all these? No one can know for sure but Nathaniel. So I don’t want to call it lying.
Lol, I’m laughing because what he’s saying is pretty bold. I’f I’m understanding right, he’s saying that there’s only two studies determining pedigree rates, and he came up with a third one based on screenshots of some raw data from a few others that didn’t explicitly try to do so. haha. That would take a lot of hubris if he was wrong and be embarrassing science.
@thoughtful that’s exactly right. It is incredible hubris.
Keep in mind his whole argument relies on evidence that scientists are eager to collect. We are measuring and refining our observations of human mutation rate now quite often, not because we are trying to prove evolution true, but because it is immensely important in understanding human disease.
There is a gigantic incentive for scientists across the globe to show that everyone else got it wrong and the mutation rates are in fact 50x faster than we expected. That would be big news. It would be in the leading journals and likely even in the news. There is no conspiracy of evolutionary scientists that could possibly prevent this, because the people who measure these rates are not even evolutionary scientists!
Yet we don’t see Nathaniel’s prediction confirmed in the literature. That doesn’t make any sense if he is right. That alone should be enough to see the problem with his argument. Just sit back and watch over the next decade. If you ever see a secular scientists in a leading journal claim that mutation rates are 50x more than we had thought for decades, and other scientists agree, then Nathaniel is vindicated. Until then, the evidence is just solidly against him, so solidly you don’t have to be an expert to see it clearly.
Nathaniel has never answered a single of my emails or messages on FB. He has obviously read my comments on how he misrepresented me (Would Jeanson Please Correct A Clear Misrepresentation?), but hasn’t fixed the misrepresentation. So I’m not sure how to ask him other than to write it on this forum.
Do you think that is trustworthy? Do you trust the science of someone who acts this way?
Incentive yes. Incredibly challenging, yes. That’s why tenure was created. But in an academic setting you’ve got to test and retest and get your ducks in a row even with tenure, I bet? You can’t just go out and be Galileo with no repercussions. It’s easier to say you did it wrong and filter the data to match, IMO.
That is a misconception. In this specific case, it would be very very easy. In fact, it would be so easy, that with new technology yet to be invented I wouldn’t be surprised if in 20 years high school students are measuring mutation rates as a take home lab for biology class. Every year it gets easier to do.
As for push back? If you had the data, and it really showed this, it would be research misconduct to manipulate the data to show something else. @glipsnort and @sfmatheson can give their comments, but I’m pretty sure the result would be quadruple checked (which is a good thing) but no one would stand in the way of its publication. It would likely be a Science or Nature paper. It would be a career maker if that result were true.
Well yes, you do have to make sure you aren’t putting out bad science, but that is always the case.
To echo what @swamidass said, it is really just a question of willpower and money. The cost of sequencing a human genome is less than a $1000 dollars. There is bioinformatics software available that anyone can purchase, and anyone can assemble the reads and compare the different genomes themselves. For that matter, scientists download their sequencing data onto public databases as part of the peer review and publishing process, so anyone can analyze it for themselves.
I would strongly suspect that Answers in Genesis pulls in more than enough money to pay for some next-gen sequencing runs. Why don’t they do it?
To be clear, it costs more usually (at least at this time) to get high coverage sequencing done. Without high coverage sequencing, errors dominate the calculation because mutations are so rare.
The software, by the way, is free.
So actual costs would likely be more. Still one could do a study for just a few hundred thousand dollars, use data collected by others, or just trust the competition between scientists trying to one up each other in the literature.
In the future though, it might be possible for far far less money.
Going by the most recent quote I have, 10x coverage (60 Gb of data, 150 bp reads) would cost just under $2,000. 20x would be twice that. This is assuming 150 bp reads would be sufficient for this purpose.
True. The free stuff tends to be less user friendly, so newbs like me prefer the paid software. We have to put up with the computer nerds looking down on us for our lack of Linux skills.
Indeed. The ingenuity among biotech companies continues to amaze me, with nanopore sequencing being one of the more recent advances.