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Human and chimp DNA: They really are about 98% similar

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A few days ago, scientist and young-earth creationist Dr. Jay Wile wrote a post on his Proslogion blog, in which he reported that Dr. Jeff Tomkins had abandoned his claim that human and chimpanzee DNA are only about 70% similar, in favor of a revised figure of 88%. But even that figure is too low, according to the man who spotted the original flaw in Dr. Tomkins’s work.

Dr. Wile reports:

More than two years ago, Dr. Jeffrey P. Tomkins, a former director of the Clemson University Genomics Institute, performed a detailed, chromosome-by-chromosome comparison of human and chimpanzee DNA using a widely-recognized computer program known as BLAST. His analysis indicated that, on average, human and chimpanzee DNA are only about 70% similar. This is far, far, below the 95-99% numbers that are commonly cited by evolutionists, so once I read the study, I wrote a summary of it. Well, Dr. Tomkins has done a new study, and it invalidates the one he did two years ago.

The new study was done because last year, a computer programmer of financial trading algorithms (Glenn Williamson) discovered a bug in the BLAST algorithm that Tomkins used. This bug caused the program to ignore certain matches that should have been identified, which led to an artificially low similarity between the two genomes.

Here is what Glenn Williamson has to say about himself:

Yeah – 36 year old, stay-at-home father of four – including triplets, ha! 🙂

I don’t have any formal qualifications in genetics, or anything biological for that matter. I have a bachelors degree in computing science (i.e. programming) from the University of Technology in Sydney. Started my career as a programmer, but transitioned into derivatives trading, which is a lot more fun…

And for what it’s worth, I believe that my paper is more of a computing science paper than a genetics paper. It’s more my area of expertise than Jeff Tomkins’ area.

Glenn Williamson’s detailed takedown of Dr. Tomkins’s 70% similarity figure can be accessed here. Dr. Tomkins claims he submitted his paper to the creationist publication, Answers Research Journal, but it was never published. Here’s an excerpt from the paper (emphasis mine – VJT):

In this paper I carefully reproduce a subset of Dr Tomkins’ results, and show clearly and unambiguously that Dr Tomkins has fallen victim to a serious bug in the software used to obtain his results. It is this bug that causes Dr Tomkins to report the erroneous figure of 70% similarity. After correcting for both the effects of this bug and some non-trivial errors in Dr Tomkins’ methodology, I report an overall similarity of 96.90% with a standard error of ±0.21%. This figure includes indels, and the result is largely in line with the secular scientific consensus.

What happened next? Dr. Wile takes up the story:

As a result, Dr. Tomkins redid his study, using the one version of BLAST that did not contain the bug. His results are shown above… The overall similarity between the human and chimpanzee genomes was 88%.

In an update at the top of his post, Dr. Wile now admits to having cold feet, even about the revised 88% figure:

Based on comments below by Glenn (who is mentioned in the article) and Aceofspades25, there are questions regarding the analysis used in Dr. Tomkins’s study, upon which this article is based. Until Dr. Tomkins addresses these questions, it is best to be skeptical of his 88% similarity figure.

So what was wrong with Dr. Tomkins’s new study? I’ll let Glenn Williamson explain (emphasis mine – VJT):

October 16, 2015 4:22 pm

As I’ve said many times, if there is a single base pair indel in the middle of a 300bp sequence, Tomkins will say this is a 50% match.

Tomkins is most certainly aware of this, yet he chose to publish it. I think that says pretty much everything.

Another commenter named Aceofspades25 has this to add (emphases mine – VJT):

October 16, 2015 2:13 pm

The other obvious thing that Thompkins hasn’t dealt with in his BLASTN analysis, I talk about here.

There are a few cases where no match will be found because this entire sequence appears de-novo in Chimpanzees as the result of a single mutation (e.g. a novel transposable element – see here) or because humans have had a large deletion which other primates don’t. Deletions like this also likely occurred in a single mutation – see here

Thompkins (sic) would count both of these as being a 0% match (or 600 effective mutations if the sequences he was searching for were 300bp each). In reality, these probably represent just 2 mutations.

I’ll let Glenn Williamson have the final word (emphases mine – VJT):

Thanks Ace, for letting me know about this post. I reiterate here a few things about my (unpublished!) paper, and about Tomkins’ new paper.

The first thing is that he uses the “ungapped” parameter in his BLAST comparisons. As I’ve written in a few other places now, using this parameter, and calculating results in the way that Tomkins does is entirely disingenuous. If you are comparing two 300bp sequences, and one of those sequences has a single indel smack bang in the middle, Tomkins counts this as the sequences being only 50% identical.

I’ve told him at least twice that he cannot use ungapped and then calculate the result in this way. He can do one of two things:

1. Use ungapped, which ignores indels and therefore he can only report the substitution rate. (emphasis mine – VJT)If he did this, he would get a result of around 98.8%.

2. Allow gaps, and – this is what he fails to mention in his paper – get a result of around 96.9%. And this is using a very conservative method of calculation as well, since it counts a 50bp indel as having the same weight as 50 individual mutations. If you counted a 50bp indel as a single event (which it probably was), then the overall result would be pushed up towards 98%, which is the figure usually thrown around anyway.

In a comment dated 14 August 2015 (at 03:44) on an article titled, Chimp and Human DNA vs “Sophisticated Nonsense”! on a blog called Marmotism, Glenn Williamson adds:

I’ve actually written a paper on Tomkins’ 70% result, and have _ATTEMPTED_ to get it published in Answers Research Journal. Obviously they are not having a bar of it – Tomkins is the sole peer-reviewer, and he is currently refusing to provide any critique of my work – he has been silent for 8 months, while the ball is in his court ..

See the paper here:

https://www.dropbox.com/sh/dm2lgg0l93sjayv/AAATnWSJdER53EYEYZvcgiwma?dl=0

It’s the two PDFs ..

Dr. Tomkins’s latest article in Answers Research Journal (October 7, 2015) acknowledges Williamson’s work in a single sentence:

As of 2013, the issue of overall genome similarity between chimpanzee and humans seemed to be about 70% based on five different reports, three of which were based on actual data analyses. However, in 2014 , a computer programmer of financial trading algorithms discovered an apparent bug in the BLASTN algorithm and notified this author of the situation (Glenn Williamson, Tibra Capital, personal communication).

So, a submitted article only counts as a “personal communication”? Perhaps Dr. Tomkins needs to be a little more up-front about giving credit where credit is due, and acknowledging his mistakes. At any rate, the ball is definitely in his court, and his latest 88% similarity figure warrants skepticism. I have to say that Dr. Tomkins’s methodology sounds rather suspicious to me.

What do readers think?

Comments
I only just found about posts 110 and 111. I have deleted any confidential information.vjtorley
November 3, 2015
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Mice and rabbits have less time and fewer cell divisions between generation, which likely gives them a lower mutation rate. They also have a lot more offspring per female than humans. And their larger population sizes make selection better able to filter slightly deleterious alleles. If I remember, any selection coefficient less than the inverse of the population size is seen as completely neutral by selection. But I don't have a source handy for this or remember if there's a constant to multiply by in there. So if anything these factors would allow mice and rabbits to outlast us. Generally it seems like the larger animals are the most prone to extinction. Lining up with this prediction (or retrodiction) they also have smaller populations, lower reproductive rates, and more cell divisions between generation. I don't know if large animal extinction risk is a result of genetic entropy or if it's due to other factors.
nearly neutral but beneficial mutations are much more frequent.
How frequent are you proposing? I've seen some experiments propose beneficial rates of up to 5 to 13%, but these are often just knocking out genes not needed in lab conditions. Here are a couple sources I've seen with perhaps better estimates. In bacterial ribosomal genes:
We used a bacterial system in which the fitness effects of a large number of defined single mutations in two ribosomal proteins were measured with high sensitivity... most mutations (120 out of 126) are weakly deleterious and the remaining ones are potentially neutral. The DFEs [Distribution of Fitness Effects] for synonymous and nonsynonymous substitutions are similar, suggesting that in some genes, strong fitness constraints are present at the level of the messenger RNA.
From a review paper on exploring fitness landscapes via directed evolution:
"Statistically, random mutations tend to be quite harsh, usually decreasing activity and sometimes destroying it altogether. 30–50% of single amino acid mutations [within protein coding regions] are strongly deleterious, 50–70% are neutral or slightly deleterious and 0.01–1% are beneficial."
John Sanford and Wolf Ekkard Lonnig have each argued that if beneficial mutations were more common (or at least detectable) then the mutagenic breeding experiments involving billions of plants would've been more successful. The 2007 paper from the Mendel team I linked above used a beneficial rate of 1% which I think is unrealistically high. But that paper used probability selection (the mostly random one). The 2011 paper did not use any beneficial mutations, but they were specifically testing the preserving ability of Mendel's accountant. Just as deleterious mutations interfere with the selection of beneficials, having beneficials can interfere with selection against deleterious mutations. There's at least half a dozen other papers from the Mendel team I haven't had time to look at. I admit I haven't looked at how Mendel simulates heritability, if at all. Do you think different distributions have a significant effect on the simulation outcome?JoeCoder
November 3, 2015
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Had some troubles with the new version (2.0.2). Apparently, the old version (1.4.7) had to be deinstalled first. JoeCoder: Kimura showed that when selection coefficients are sufficiently small, selection treats beneficial alleles as if they are neutral. That is correct. And everyone agrees that if mutations occur too quickly, it will lead to extinction. On the other hand, mice have been around for a very large number of generations, and there is no sign of mutational meltdown — not to mention yeast, rabbits, and beetles. Notably, organisms have evolved to survive even high radiation environments. One of the problems with the model is the ratio of deleterious to beneficial mutations. While selectively significant mutations are mostly deleterious, nearly neutral but beneficial mutations are much more frequent. Consider an optimized structure. The peak of the fitness curve has a slope, and small changes can occur on either side of the peak with only small effect. Consequently, the fitness will meander around the peak, with fitness sometimes being slightly degraded, and other times slightly improved. Another problem is that heritability varies with trait, and depends on the particular environment, as well as the amount of variation in the population. This factor is in addition to the randomization, so further degrades the signal.Zachriel
November 3, 2015
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Zachriel, Kimura showed that when selection coefficients are sufficiently small, selection treats beneficial alleles as if they are neutral. So greater scrambling with smaller coefficients is exactly what Mendel's Accountant should be doing. Based on the experiments I reported in comment #136, even probability selection (the most random mode) looks to me to be at least within the realm of what's biologically realistic. All 25 deleterious mutations were removed and 40% of the beneficial mutations fixed. Do you have a way to exactly quantify how much randomness is too much or not enough in the selection process?JoeCoder
November 3, 2015
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Zachriel: We haven’t looked at the code in several years (2009). We’ll take another look at some point. Do you remember my asking you the last time you had looked at the code and you telling me that it had not changed?Mung
November 3, 2015
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Assuming a parameter of 0.5, the result will still be essentially scrambled when the selection coefficient is small. It's also dependent on population size, and the founder effect.Zachriel
November 3, 2015
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JoeCoder: The second term is 1 minus the parameter. Okay. It dropped out in your shortened formula. p+(1-p)*randnum() We haven't looked at the code in several years (2009). We'll take another look at some point.Zachriel
November 3, 2015
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If the parameter is 0.1, then the value is 0.1 to 0.2 If the parameter is 0.9, then the value is 0.9 to 1.8 If the parameter is 1.0, then the value is 1.0 to 2.0
These calculations are incorrect. The second term is 1 minus the parameter. If the parameter is 0.1, then you get (0.1 + 0.9 * randomnum()) and fitness is divided by a random number from 0.1 to 1.0. If the parameter is 0.9, then it's divided by a random number from 0.9 to 1.0
JoeCoder: The Mendel authors describe: “Probability selection contrasts strongly with truncation selection wherein there is no element of randomness.
Maybe you've got the modes mixed up? We have: probability selection - very random (selection_state == 2) truncaction selection - non-random (selection_state == 1) partial truncation selection - a blend between the two modes above. (selection_state == 4) The formula I worked out above is partial truncation selection. If you use Chrome's web inspector on Mendel's user interface, you can verify that truncation selection is selection_state==1. So in selection.c it doesn't execute any of those three "if (selection_state == ?)" paths that add randomness to the fitness. There's also strict proportionality probability selection (selection_state == 3), but I haven't seen the Mendel authors report using this mode. Although i haven't read all their other papers.JoeCoder
November 3, 2015
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JoeCoder: So if you plug that into the formula above, the fitness is divided by: (0.5 + (0.5 * randomnum())) So when partial truncation selection is used (most runs), they are dividing by a random number uniformly distributed between 0.5 and 1.0 If the parameter is 0.5, then the value is 0.5 to 1.0 If the parameter is 0.1, then the value is 0.1 to 0.2 If the parameter is 0.9, then the value is 0.9 to 1.8 If the parameter is 1.0, then the value is 1.0 to 2.0 Selection is by ranking, so what is the effect of the parameter? JoeCoder: The Mendel authors describe: “Probability selection contrasts strongly with truncation selection wherein there is no element of randomness. Still don't see the justification for this statement.Zachriel
November 3, 2015
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@Zachriel Sorry I didn't respond sooner. I had thought this thread was dead and hadn't checked it. In the Mendel source code, take a look at selection.c lines 516 through 530:
if (selection_scheme == 4) { // partial truncation selection // ... work_fitness[i] /= partial_truncation_value + (1. - partial_truncation_value) * randomnum();
randonnum() is defined in ranlib.c line 6: #define randomnum() (float)(rand()/(float)RAND_MAX). The built in function rand() returns a number between 0 and RAND_MAX (a very large integer), so the randomnum() function returns a random number between 0 and 1 with a uniform distribution. In the 2011 paper the authors used “partial truncation (unless otherwise specified)” with “partial truncation input parameter = 0.5?. So if you plug that into the formula above, the fitness is divided by: (0.5 + (0.5 * randomnum())) So when partial truncation selection is used (most runs), they are dividing by a random number uniformly distributed between 0.5 and 1.0 and still have the declining fitness shown in figure 6. However in a few cases they do use unrestricted probability selection (selection_scheme == 2) for comparison,and there they do divide between 0 and 1. I think it's very biologically realistic to scramble the ranking more when the differences in fitness are smaller. I don't know how to calculate whether unrestricted probability selection is biologically realistic, but partial truncation selection is overly generous and still shows decline. The Mendel authors summarize:
With a [deleterious] mutation rate of 10, almost half of all deleterious mutations were retained, with a nearly constant accumulation rate of 4.5 mutations per individual per generation.
In other words, we can't have more than 10 - 4.5 = 5.5 deleterious mutations per generation. This seems consistent with estimates of various evolutionists. Forty-three years ago Susumu Ohno calculated that no more than 6% of our DNA could be nucleotide-specific functional:
the moment we acquire 10^5 gene loci, the overall deleterious mutation rate per generation becomes 1.0 which appears to represent an unbearably heavy genetic load... at the most, only 6% of our DNA base sequences is utilized as genes
If you read the context you can see that by "genes" he means functional entities, not necessarily only protein coding exons. If I'm reading him right, Larry Moran seems to prefer an even smaller number:
if the deleterious mutation rate is too high, the species will go extinct... It should be no more than 1 or 2 deleterious mutations per generation.
Ford Doolittle, Dan Graur, and T. Ryan Gregory have made similar comments.JoeCoder
November 2, 2015
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Z: the division of working fitness by a random number from zero to one. We haven't devised a definitive test, but a quick experiment shows that when fitnesses vary only slightly, as with nearly neutral mutations, then the divide-by-random function tends to scramble the ranking more than when fitnesses vary widely, as with strong selection.Zachriel
October 29, 2015
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Right, now the authors don't know what they are talking about. Nice "argument", Zachriel.Virgil Cain
October 29, 2015
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JoeCoder: The Mendel authors describe: “Probability selection contrasts strongly with truncation selection wherein there is no element of randomness. While we haven't reviewed the entire project, this statement is false due to the division of working fitness by a random number from zero to one.Zachriel
October 29, 2015
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JoeCoder, Lighten up, Mapou was joking. The "LOL" should have been a clue. Also doxing insipid trolls should be mandatory.Virgil Cain
October 28, 2015
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@Mapou Even though I'm on your side (ID), you are now calling for me to be doxed because I think ideas within ID should be subjected to review from knowledgeable but friendly critics to help test their validity?JoeCoder
October 28, 2015
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Turns out that fruit flies and rats are biological organisms
Ya think? :/ Normally, I'd say the mental gymnastics (MGs) in your brain settled down to realize this oh so obvious fact but I remembered you're a multi-person entity so the version that posted that must've done a Google search on what rats and fruitflies are. Congrats, Zachriel XY v.2.0. :)
Notably, you have to response [sic] to how the Lederberg Experiment shows that mutations are random with respect to fitness.
Yup, at this point, it's obvious Zachriel XY v.2.0 was talking to another Zachriel because of the reactivation of the MGs. The mental gymnastics caused a "too_much_reality" overload as that'll explain why you're asking yourself a very good question concerning a delusional idea proposed by another Zachriel which BTW Mike has already refuted in the other thread.Vy
October 27, 2015
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Mapou:
Does anybody know the identities of Mung and JoeCoder?
I know the identity of Mung.Mung
October 27, 2015
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Come on guys, if the comments need to be taken down, take them down already.computerist
October 27, 2015
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Does anybody know the identities of Mung and JoeCoder? LOL Anonymous cowards calling for banning me from UD? You must be joking. I don't care. UD is mostly recreation for me when I need a break from my work. I enjoy bashing atheists and Darwinists.Mapou
October 27, 2015
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@Mapou at 178 As an ID proponent I very much appreciate wd400's participation here. When I have an interesting idea there's nobody here who is as knowledgeable yet still friendly as he/she is for me to test it against. And testing against critics is IMHO the best way to tell whether an idea is true. In contrast, we have several other ignorant but friendly critics, and perhaps a couple other knowledgeable but rude critics.JoeCoder
October 27, 2015
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Upright BiPed:
Moderators, comments #110 and #111 need to be removed from this thread.
I second that motion. And Mapou should be warned and if it happens again, banned. This should not be tolerated.Mung
October 27, 2015
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Vy: Who knows what next you’re gonna bring up, fruit flies? Rats?? Turns out that fruit flies and rats are biological organisms, hence, relevant to a discussion biology. Notably, you have to response to how the Lederberg Experiment shows that mutations are random with respect to fitness.Zachriel
October 27, 2015
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wd400 @176 whining about the right to be anonymous:
I don’t know (or care) if the information is true, but allowing this sort of behviour is dangerous (people value their anonymity for any number of good reasons) and will see many comenters leave.
You, too, should be outed since you're nothing but a troll. And good riddance.Mapou
October 26, 2015
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That was a misstatement.
Nope, it's pretty much standard Zachriel.
We appended a correction.
We did, eh?
Thousands of experiments show that mutations are random with respect to fitness. The Lederbergs Experiment happens to be one that is easy to understand, and easy to replicate.
*yawn* The park is closed. No more going around circles with you, especially someone like you. Who knows what next you're gonna bring up, fruit flies? Rats?? Uh uh, I have better things to do.Vy
October 26, 2015
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Having only just seen comments 110 and 111 here, can I join the list of commenters who would like to see those posts deleted and a clear policy of that people outing real-world identities should expect to be banned in future? I don't know (or care) if the information is true, but allowing this sort of behviour is dangerous (people value their anonymity for any number of good reasons) and will see many comenters leave.wd400
October 26, 2015
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Vy: "In the case of many adaptations, we can show they are random with respect to fitness. " That was a misstatement. It should read "In the case of many mutations, we can show they are random with respect to fitness." We appended a correction. Vy: A few umpteen comments ago, it was the Lenski experiments that showed it and now it’s this one. Thousands of experiments show that mutations are random with respect to fitness. The Lederbergs Experiment happens to be one that is easy to understand, and easy to replicate. mike1962: You should have put “many” in front of “mutations.” Or: The Lederberg experiment shows that the specific mutations in the study are random with respect to fitness. Of course, many other experiments have been done to confirm this applies to mutations generally. mike1962: Which leaves up in the air how the little beasts managed to “evolve resistance” in the first place and maintain that resistance in a subset of the population when no need existed for it. Antibiotic resistance degrades over time. However, antibiotics are common in the natural environment as well as in human society, so many forms of resistance persist.Zachriel
October 26, 2015
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Zachriel @152: Evolution refers to hereditary changes. In the case of many adaptations, we can show they are random with respect to fitness. That statement should read "In the case of many mutations, we can show they are random with respect to fitness."Zachriel
October 26, 2015
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Zechriels: The Lederberg experiment shows that mutations are random with respect to fitness. You should have put "many" in front of "mutations." In 1952, Esther and Joshua Lederberg performed an experiment that helped to show that many mutations are random, not directed. http://www.evolution.berkeley.edu/evosite/evo101/IIIC1bLederberg.shtml They did not evolve resistance in response to exposure to the antibiotic. Which leaves up in the air how the little beasts managed to "evolve resistance" in the first place and maintain that resistance in a subset of the population when no need existed for it. https://uncommondescent.com/evolution/spetners-non-random-evolutionary-hypothesis/#comment-584909mike1962
October 26, 2015
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Nearly every single sexually reproducing organism is a unique combination of traits, and nearly all carry a number of mutations, yet the vast majority are viable.
So? Have you not read what I stated about public/private/protected regions? That allows your scenario to be viable, without it your scenario would not be viable.computerist
October 26, 2015
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So random mutations are no longer random. They are now only random with respect to fitness, whatever that means. This is a favorite tactic of liars: when you're caught in a lie, change the names in order to confuse people. This is why global warmists change "global warming" to "climate change" and why Darwinists are renaming random mutations. It's called science by relabeling which is no better than the previous science by labeling. To explain something you are clueless about just give it a name. My favorite example so far is "convergence".Mapou
October 26, 2015
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