Ok, my mistake
Ok. But, it seems though that it is theoretically possible to run MA with settings where fitness increases (see below)
The accompanying text shows that MA allows users to control for the fraction of beneficial and deleterious mutations that is above a certain threshold, meaning that, contrary to what @Rumraket and @CrisprCAS9 said, MA makes room for beneficial mutations having a fitness effect >=0,1.
So you’re saying you’re completely unable to understand the words you are typing?
Fraction of beneficials > 0.1
Maximum effect of beneficials > 0.1
Do you understand the difference between the two things above, do you recognize which you just referenced, and do you recognize which we were talking about?
Take your time.
Omicron has almost completely taken over. But that’s irrelevant, because there are variants out there with more mutations than you think should be possible. The mere fact of their existence means you lose.
Do you? I’m going to bet you will say something stupid now and then I will have to try to drill into your dulled intellect something about population size, genome size, and mutation rate that means most “fixed” mutations never truly reach 100% of individuals.
Proteins still need to function in bacteria and viruses too, you idiot.
Great suggestion. Then how about you fire up google maps and find the nearest bridge. Bye. 
Obviously because the walk and fresh air would do him some good and the view from a bridge is usually pretty great and no other reason, I’m sure…
Here’s a variant with 51 mutations in the spike protein:
hCoV-19/SouthAfrica/NICD-R10185/2023
S
Changes (51):T19I, R21T, A27S, S50L, V127F, G142D, F157S, R158G, L212I, V213G, L216F, H245N, A264D, I332V, G339H, K356T, S371F, S373P, S375F, T376A, R403K, D405N, R408S, K417N, N440K, V445H, G446S, N450D, L452W, N460K, S477N, T478K, N481K, E484K, F486P, Q498R, N501Y, Y505H, E554K, A570V, D614G, P621S, H655Y, N679K, P681R, N764K, D796Y, S939F, Q954H, N969K, P1143LReversions to root (2):R346R, Q493Q
Gaps (5 regions, 8 codons):24…26 (3 codons), 69…70 (2 codons), 144, 211, 483
Another “statistical miracle”. How did it wander 51 steps away from the starting point in sequence space without breaking the protein, Bill?
God did it.
Sure they do. Are the functions the same? Basketball and baseball are both games. Are they played in the same way?
Have you heard of the fallacy of false equivalence?
Weren’t you the one bringing up phone numbers as examples, to illustrate some point about sequences?
Have you heard of the concept of irony?
Hi Ron
Thanks for this graph. What we have seen is many variants to a virus. How do you think this supports the single origin claim that the variation we see in life is due to reproductive mechanisms and natural variation?
Yes and I have seen the act of a young and potentially talented guy that is trying to be a hero and will ultimately fail badly as he is not thinking through what he is presenting.
I think it is you who should take the time to review the passage I am referring to entitled « prescribing fitness effects of mutations », with a particular focus on the two quantities that define gamma, ie., theta and q.
Ah, the melodious call of Zalophus californianus.
Three questions, please answer them all:
First, no matter what they might say elsewhere, you gave the fact that they allowed the fraction of beneficials to be greater than 0.1 as evidence that they allowed the effect of beneficials to be greater than 0.1.
Do you accept that this was an error, or not?
Second, no matter what what they might say elsewhere, I gave you the screenshot of MA showing that the effect size of beneficial alleles was restricted to 0.01.
What do you make of this screenshot?
Third, if you look in the text of the ‘article’, they state that the effect size of beneficials is restricted to 0.1 (see images).
What do you make of this fact?
It would be more accurate to say that your interpretation of what I said was tendentious, and motivated by a desire to twist it to make it appear fallacious.
“The only reason John Sanford is not recognize[sic] as an expert in population genetics by mainstream scientist[sic] …”
… is that he appears to have no training or research experience in the field. Sanford’s expertise lies in “plant breeding/plant genetics” (i.e. artificial selection rather than natural selection and natural variation). His only foray into population genetics appears to be GE & MA – neither of which appear to have any evidentiary basis, and the legitimacy of both being heavily disputed.
It really is the weirdest program. I can’t find a version history anywhere so I can see what changes were made and when.
This prompted me to once again download the latest version I could find. Re-confirming all my previous complaints that it is a trash piece of software for both reasons of theoretical evolutionary genetics, and practicality.
The program now seems to allow values much higher than previously without complaint, though it still contains vestiges of it’s earlier limitations, such as the pop-up that informs us what the previous allowed range of values was. That’s why I’d like to see a version history.
Anyway. First of all, why is there a field called “Total non-neutral mutation rate (per individual per generation”?
Shouldn’t the neutrality of a mutation be defined by the relationship between the mutation’s magnitude of effect and population size? Why isn’t it just called the “mutation rate” full stop?
Second, the maximum allowed reproductive rate (the maximum number of offspring produced by an individual) is 6. That’s ridiculous. How can you have predefined maximum of 6 and pretend it’s a realistic simulation for anything?
The memory limitations are obscene. It refuses to run with anything approaching realistic values. I have 32 GB of ram and yet it is literally impossible to run the software with realistic population values for things like bacteria and viruses, or innumerable eukaryote species. And the sorts of ranges that seem able to run (a few ten thousand at most) are not far from the zone where many species would be considered endangered anyway. The software therefore seems unable to run in anything but what could be considered a constant bottleneck mode. The very same area where conventional population genetics agrees there is a real danger of extinction due to selection being swamped by the power of drift. You can’t meaningfully simulate evolution for anything, even most eukaryote species have population sizes well above 25000 individuals.
That’s just a bit too convenient if you ask me.
Heritability is set at 0.2 by default. To my knowledge most mutations have a heritability of 1.0 unless they directly affect fertility in some way. This is Sanford doing an observable trait (such as height, a genetic multi-locus trait with a strong influence of environment) vs germline mutation bait-and-switch. Mutations are heritable, but their cumulative phenotypic effects, the TRAITS they result in, have other influences besides genetic, meaning offspring won’t inherit the exact height of their parents. This is Sanford lying with software. Or being incompetent. Take your pick.
Then there are the odd results you obtain if you run the simulation with whatever values you set. To really see how something must be wrong under the hood, so to speak, compare runs with two radically different values. For example, what would happen if 30% of all mutations were beneficial? Then compare it to more default values.
Here’s such a comparison. First some values (everything not specified here is left at default values). First run:
Total non-neutral mutation rate pr individual pr generation: 0.01
Beneficial to Deleterious ratio: 0.001 (1:1000)
Reproductive rate: 6
Population size: 10000
Generations: 1000
Functional genome size: 30E+04 (basically a virus genome)
Maximum beneficial fitness effect: 0.1
Allow back mutations?: Yes.
Heritability 1.0
Recombination model: Clonal reproduction
I’ll change the bolded number for the next run.
Results:
On the first figure we see deleterious mutations accumulate steadily, while beneficial mutations don’t. On the second figure mean population fitness remains constant. Weird. (The red line indicating fitness isn’t visible because it is exactly underneath the blue line).
Run two:
Beneficial to Deleterious ratio: 0.3 (3:7) So
30% of all mutations are now beneficial, where before it was one in one thousand mutations.
Results:
Amateur.
It’s definitely this one.
I think it has more to do with his fallacious genetics.
There comes a point where you do have to consider the source.
