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Wesley R. Elsberry Posts: 4991 Joined: May 2002 (Permalink) Posted: June 12 2009,22:07    I'll check with Reed Cartwright about existing popgen packages. Avida is not a package that aims to directly model biological population genetics. There is quite a lot of conceptual overlap between Avida evolution and biological evolution, but it isn't at the low-level that MA claims to operate at. For example, current research in Avida is looking at the role of compensatory mutations. But each mutation in an Avidian is an instruction, not a base as in DNA. The Avida research can provide another line of evidence that complements that of biological research on compensatory mutations, but it isn't aimed at answering questions like, "At what rate should we expect compensatory mutations to fix in species X?" It's that kind of question that the folks pushing MA position it as a tool to answer, or would if they took any note of compensatory mutations at all. I think you get the drift, though. Avida, by the way, has no difficulty in cranking out data on generation after generation for a set population size. Most Avida work is done on population sizes between 900 and 10,000 Avidians. However, I'm working on extending the Avida-ED program, and one part is to allow up to 90,000 organisms in the population. That is, by the way, accomplished with a change to the graphical user interface to allow selection of a grid size of up to 300 by 300, where the current version's grid-size slider only goes up to 100. The underlying Avida instance is unchanged. Tracking mutations is possible in Avida as well, but is done in analysis after the run finishes. Runs can go into the millions of updates. I don't know that anyone has tried to find an upper limit. Avida's ability to do this is because it only needs to hold the current population and grid in memory. Everything else gets written to disk. -------------- "You can't teach an old dogma new tricks." - Dorothy Parker

midwifetoad Posts: 4003 Joined: Mar. 2008 (Permalink) Posted: June 12 2009,23:43    Who woulda thunk a few years ago that entry level computers would have four gigs of memory, or that the retail price of four gigs would be about $19.95? -------------- Any version of ID consistent with all the evidence is indistinguishable from evolution.

dvunkannon Posts: 1377 Joined: June 2008 (Permalink) Posted: June 13 2009,00:12    Quote (Wesley R. Elsberry @ June 12 2009,23:07) I'll check with Reed Cartwright about existing popgen packages. Avida is not a package that aims to directly model biological population genetics. There is quite a lot of conceptual overlap between Avida evolution and biological evolution, but it isn't at the low-level that MA claims to operate at. For example, current research in Avida is looking at the role of compensatory mutations. But each mutation in an Avidian is an instruction, not a base as in DNA. The Avida research can provide another line of evidence that complements that of biological research on compensatory mutations, but it isn't aimed at answering questions like, "At what rate should we expect compensatory mutations to fix in species X?" It's that kind of question that the folks pushing MA position it as a tool to answer, or would if they took any note of compensatory mutations at all. I think you get the drift, though. Avida, by the way, has no difficulty in cranking out data on generation after generation for a set population size. Most Avida work is done on population sizes between 900 and 10,000 Avidians. However, I'm working on extending the Avida-ED program, and one part is to allow up to 90,000 organisms in the population. That is, by the way, accomplished with a change to the graphical user interface to allow selection of a grid size of up to 300 by 300, where the current version's grid-size slider only goes up to 100. The underlying Avida instance is unchanged. Tracking mutations is possible in Avida as well, but is done in analysis after the run finishes. Runs can go into the millions of updates. I don't know that anyone has tried to find an upper limit. Avida's ability to do this is because it only needs to hold the current population and grid in memory. Everything else gets written to disk. Umm, what happened to Model-View-Controller? The idea that the model is costrained by the UI is pretty scary. -------------- I’m referring to evolution, not changes in allele frequencies. - Cornelius Hunter I’m not an evolutionist, I’m a change in allele frequentist! - Nakashima

Wesley R. Elsberry Posts: 4991 Joined: May 2002 (Permalink) Posted: June 13 2009,00:37    Avida-ED is not meant to be how researchers usually use Avida. Avida-ED is a GUI interface aimed at making use of a limited set of Avida options easy for pedagogy. There are quite a number of simplifying restrictions that Avida-ED imposes for the runs that can be made with it, but there are still enough parameters under instructor or student control to allow a great many different experiments to be done with it. Links to both Avida and Avida-ED via the Devolab -------------- "You can't teach an old dogma new tricks." - Dorothy Parker

Steve Schaffner Posts: 13 Joined: June 2009 (Permalink) Posted: June 13 2009,07:01    There is a good list of forward simulation (as opposed to coalescent) programs here. The ones I'm familiar with (apart from MA) are intended to model the behavior of sequences and mutations, not the global evolution of species.

Dr.GH Posts: 2333 Joined: May 2002 (Permalink) Posted: June 13 2009,09:21    Quote (Wesley R. Elsberry @ June 12 2009,14:28) - Develop a test suite based on published popgen findings in parallel with development This seems to me to be an excellent way to test MA- known data parameters from known populations. Also, what were the release dates for the different versions of MA compared to the different publication/conference dates? Edited by Dr.GH on June 13 2009,07:24 -------------- "Science is the horse that pulls the cart of philosophy." L. Susskind, 2004 "SMOLIN VS. SUSSKIND: THE ANTHROPIC PRINCIPLE"

Tracy P. Hamilton Posts: 1239 Joined: May 2006 (Permalink) Posted: June 13 2009,10:28    Quote (Bob O'H @ June 12 2009,17:02)   What's new is his claim that meltdown affects sexual populations.  I should check the evolution of sex literature, I'm sure they (Sally Otto and Nick Barton, amongst others) showed that it doesn't happen.  In his book Sanford ignores the recent evolution of sex literature. Is Sanford practicing abstinence from the sex literature?   -------------- "Following what I just wrote about fitness, you’re taking refuge in what we see in the world."  PaV "The simple equation F = MA leads to the concept of four-dimensional space." GilDodgen "We have no brain, I don't, for thinking." Robert Byers

Zachriel Posts: 2723 Joined: Sep. 2006 (Permalink) Posted: June 14 2009,08:47    When each child has more than a single mutation, then average fitness can decrease over time. Even though fitness is a relative term, this decreasing fitness can impact essential biological mechanisms. If the genome is 3e8 bases in size (or any such large number) and there is an average of one mutation per child, then we expect that ~1/3 of the children will *not* have mutations. If each mother produces 6 children, then chances are that each new generation will include many individuals without mutations. (E.g. mice often have several litters of 4-10 pups.) If we use truncated selection, heritability=1, mutations=1, seed=30, all else default, this is what we see. It's interesting to see how the deleterious mutations ride along with the beneficial mutations until fixation before being weeded out. In nature, we expect that if the mother produces enough children, then there should be sufficient healthy progeny to prevent genetic meltdown and to allow the positive ratcheting of beneficial mutations. We might also expect that species will tend to push the envelope with regard to mutational limitations. That means when near the margins small changes in parameters will allow it tip one way or the other. With slow reproducers, we can then expect various factors that mitigate the long-term evolutionary trajectory with regard to the accumulation of deleterious mutations. One such factor is sexual selection which is prevalent in nearly all taxa of interest. We can reasonably show that selection of a wide number of parameters avoids mutational meltdown and we would expect life to evolve to explore the limits of these parameters. Hence, to claim that a simplified simulation such as Mendel's Accountant can disprove evolution is not justified. We're still rather curious about the selection parameters,    Truncation    Unrestricted probability    Strict proportionality probability    Partial truncation i.e. exactly what each selection criterion is doing. -------------- You never step on the same tard twice—for it's not the same tard and you're not the same person.

Zachriel Posts: 2723 Joined: Sep. 2006 (Permalink) Posted: June 14 2009,09:48    Also curious about the "heritability" parameter. Quote Mendel's Accountant User Manual: Individual genetic fitness values are calculated based upon each individual’s total mutation inventory. Individual genetic fitness is defined as 1.0, adjusted by the positive and negative effects of all its mutations. To obtain phenotypic fitness the genetic fitness is modified using the specified heritability to account for nonheritable factors such as variations in the environment. What is the other 80%? Randomness? -------------- You never step on the same tard twice—for it's not the same tard and you're not the same person.

Bob O'H Posts: 2564 Joined: Oct. 2005 (Permalink) Posted: June 14 2009,10:20    It should be.  I wonder how they calculate it, though.  The description makes it look like they calculate the genotypic variation in fitness, and then multiply it by 4 to get the environmental variance, and create a random environmental effect for each individual with that variance.  But that's nuts, because it means that the amount of environmental variation in fitness is directly tied to the amount of genetic variation. it's possible, though, that they're doing nothing like this: the description is rather confused. -------------- It is fun to dip into the various threads to watch cluelessness at work in the hands of the confident exponent. - Soapy Sam (so say we all)

mammuthus Posts: 13 Joined: June 2009 (Permalink) Posted: June 15 2009,18:38    More from Sanford.  Apparently, MA is the "state of the art" in numerical genetics. Also, he wants to collaborate with y'all. According to Jorge:   Quote The last thing that JS did was ask me for the email address of the people performing these simulations & asking the questions so as to jointly work towards the goal of a more realistic & acceptable-by-all Mendel program. Collaborative science at it best. anyway, here is his latest.  In italics are the points being responded to (from Steve Schaffner) Quote Dear Colleague - If we can make the program more realistic, we will. Please explain what you would like done ... How would you have us model soft selection? I fail to see why mutations should not cause extinction, especially given the additive model. As we approach zero mean fitness, many individuals will have a fitness of zero or less - we are forced to truncate them (if you are dead you should not realistically reproduce), causing population size to start to rapidly shrink. When there are less than two individuals, we consider the population extinct. 2) The default value for the maximum beneficial value of mutations is much too low. Real-world estimates of positive selection coefficients for humans are in the range of 0.1, not 0.001. That is easily re-set, but one has to consider if it is reasonable to realistically build up a genome by increments of 10% (I am speaking of internal complexity - not adaptation to an external environmental factor). I think that is like going up Mt. Improbable using a helicopter. 3) The starting population is genetically perfect, and all deviations from that state increase the chance of extinction. This does not accurately model an evolutionary process, in which no population ever achieves perfection, merely adequacy. The fact that an ideal organism would have a major competitive advantage compared to the real one does not imply that the real one is nonfunctional or doomed to extinction. This is not a model of biological evolution. We do not assume an ideal starting genotype - we assume a uniform population after a population bottleneck - with fitness set arbitrarily at 1.0. Finally, I also have a technical problem with the program as a software tool. It does not seem to be possible to run it indefinitely, nor have I seen any cases where it has even been able to run to equilibrium (or better, steady state). Whether that is because it continues to track mutations after they fix I don't know (that's my guess), but it means it is essentially useless as a research tool. It should be possible to simulate a population of size, say, 20,000 for 200,000 generations. What would the memory requirements for that set of parameters be? Is the program really able to use the extra memory? We can turn off individual mutation tracking and just track the net fitness of each linkage block. We get nearly indeterminate processing - but we lose lots of interesting data. I would be happy to cooperate with you - if you are interested. As far as I can determine, Mendel is now the "state of the art" in genetic numerical simulation, and it improves every month. Are you aware of a better research platform? Best wishes - John Sanford http://www.theologyweb.com/campus....unt=161 For full context, here is the material Sanford is responding too: Quote I haven't raised any claims of fraud, nor am I clamoring for an immediate response. I have the following problems with model, based on what I've seen here. 1) There does not seem to be an option for true soft selection. Even if deleterious alleles do not affect fertility, they still cause the population to become extinct. This is not an accurate model of real genetics. 2) The default value for the maximum beneficial value of mutations is much too low. Real-world estimates of positive selection coefficients for humans are in the range of 0.1, not 0.001. 3) The starting population is genetically perfect, and all deviations from that state increase the chance of extinction. This does not accurately model an evolutionary process, in which no population ever achieves perfection, merely adequacy. The fact that an ideal organism would have a major competitive advantage compared to the real one does not imply that the real one is nonfunctional or doomed to extinction. This is not a model of biological evolution. Finally, I also have a technical problem with the program as a software tool. It does not seem to be possible to run it indefinitely, nor have I seen any cases where it has even been able to run to equilibrium (or better, steady state). Whether that is because it continues to track mutations after they fix I don't know (that's my guess), but it means it is essentially useless as a research tool. It should be possible to simulate a population of size, say, 20,000 for 200,000 generations. What would the memory requirements for that set of parameters be? Is the program really able to use the extra memory? If Sanford (or co-author) wishes to address these criticisms, I would welcome the response. As it stands, however, I do not see how one can use this model to make any statements about the likely behavior of evolving populations in the real world.

Zachriel Posts: 2723 Joined: Sep. 2006 (Permalink) Posted: June 15 2009,21:00    Quote John Sanford: That is easily re-set, but one has to consider if it is reasonable to realistically build up a genome by increments of 10% (I am speaking of internal complexity - not adaptation to an external environmental factor). I think that is like going up Mt. Improbable using a helicopter. Which goes to show that he doesn't understand his own simulation. Mendel's Accounant doesn't model "internal complexity". It purports to abstract selective differences. A specific limit to beneficial mutations may not make sense. Some mutations may sweep over a population rapidly. It is certainly conceivable that a seemingly minor mutation could dramatically increase reproductive success, perhaps many-fold, such as when there is only one male that reproduces. -------------- You never step on the same tard twice—for it's not the same tard and you're not the same person.

midwifetoad Posts: 4003 Joined: Mar. 2008 (Permalink) Posted: June 16 2009,01:11    There are two flavors of Creation Math: Proving that observed phenomena are impossible, and proving that unobserved phenomena are inevitable. -------------- Any version of ID consistent with all the evidence is indistinguishable from evolution.

Dr.GH Posts: 2333 Joined: May 2002 (Permalink) Posted: June 16 2009,10:26    Quote (mammuthus @ June 15 2009,16:38) "More from Sanford.  Apparently, MA is the "state of the art" in numerical genetics. Also, he wants to collaborate with y'all. According to Jorge: ..." This is interesting, but it is a wasted effort if filtered through Jorge F. If Sanford wanted to, he would register at TWeb. I don't see the need to invite him here. But, that might be preferable to TWeb because we could be better assured of moderator/admin issues (ie. no need to bother filtering the JorgF crap). -------------- "Science is the horse that pulls the cart of philosophy." L. Susskind, 2004 "SMOLIN VS. SUSSKIND: THE ANTHROPIC PRINCIPLE"

sledgehammer Posts: 533 Joined: Sep. 2008 (Permalink) Posted: June 16 2009,14:42    Quote (Zachriel @ June 15 2009,19:00)           Quote John Sanford: That is easily re-set, but one has to consider if it is reasonable to realistically build up a genome by increments of 10% (I am speaking of internal complexity - not adaptation to an external environmental factor). I think that is like going up Mt. Improbable using a helicopter. Which goes to show that he doesn't understand his own simulation. Mendel's Accounant doesn't model "internal complexity". It purports to abstract selective differences. A specific limit to beneficial mutations may not make sense. Some mutations may sweep over a population rapidly. It is certainly conceivable that a seemingly minor mutation could dramatically increase reproductive success, perhaps many-fold, such as when there is only one male that reproduces. I think it is even worse that that Zach, for three reasons: Firstly, the parameter in question is the "maximal fitness effect of a beneficial mutation". This has nothing to do with the physical makeup of the genome, as Dr Sanford seems to imply.  It seems absurd to link this parameter to some implication of "affected base pairs", much less some inferred "infusion of information" into the genome, as the description of this parameter in the MA manual below seems to imply:           Quote Mendel's Accountant User Manual: Maximal beneficial mutation effects – A realistic upper limit must be placed upon beneficial mutations. This is because a single nucleotide change can expand total biological functionality of an organism only to a limited degree. The larger the genome and the greater the total genomic information, the less a single nucleotide is likely to increase the total. Researchers must make a judgment for themselves of what is a reasonable maximal value for a single base change. The MENDEL default value for this limit is 0.001. This limit implies that a single point mutation can increase total biological functionality by as much as 0.1%. In a genome such as man’s, assuming only 10% of the genome is functional, such a maximal impact point mutation might be viewed as equivalent to adding 300,000 new information-bearing base pairs each of which had the genome-wide average fitness contribution. Researchers need to honestly define the upper limit they feel is realistic for their species. However it should be obvious that, in all cases, the upper limit for beneficial mutation effects ought to correspond to a very small fraction of the total genomic information (i.e. a small number relative to one). Call me cynical, but when this much handwaving is applied to a point,  I suspect it means that this is a crucial parameter when it comes to justifying the conclusion that "genetic entropy" leads inevitably to genetic meltdown. Secondly, there seems to be no reason to limit the maximal fitness effect of a beneficial mutation to a very small number.  Clearly, as pointed out by Z and others, in a competitive environment, there seems to be no reason a single beneficial mutation cannot virtually guarantee reproductive success. In other words, why can't the maximal fitness benefit of a beneficial mutation be something close to unity? Lastly, the parameter in question is implemented as a scale factor on the probability distribution of fitness effect, which, for no apparent reason, is hard coded to be identical to the shape of the PDF of fitness effects of deleterious mutations  (whose scale factor is hard coded to be -1, i.e. instant death).  The effect of this fitness effect PDF scaling is even more significant when one considers that the PDF shape is already heavily skewed so that the vast majority of mutations fall "under the radar" of selection. So now, all beneficial mutations are 1000-fold (default value 0.001) less likely to become fixed in the population through selection, hard or soft.  That seems unrealistic to me, so say the least. To mitigate the above bias against beneficials,  I recommend setting the maximal beneficial fitness parameter close to unity, which will symmetrize the fitness effect probability distribution, and then play with the parameter that determines the proportion of beneficial mutations ( i.e. set the ratio of beneficial to deleterious mutations to .001 or whatever).  My guess is that this will "level the playing field" and have a significant effect on the overall fitness trend. Maybe someone who has MA up and running (Zach, Sam?) could try this and report? P.S. I occurs to me that the PDF shape symmetry might also help account for the effects of the mutational "flipping" of deleterious to beneficial and vice versa. ETA clarification: "be fixed by selection" is now "become fixed in the population through selection" -------------- The majority of the stupid is invincible and guaranteed for all time. The terror of their tyranny is alleviated by their lack of consistency. -A. Einstein  (H/T, JAD) If evolution is true, you could not know that it's true because your brain is nothing but chemicals. ?Think about that. -K. Hovind

JohnW Posts: 3217 Joined: Aug. 2006 (Permalink) Posted: June 16 2009,15:47    Quote (sledgehammer @ June 16 2009,12:42) I think it is even worse that that Zach, for three reasons: <snip> I think you're right, sledgehammer.  It looks like Sanford thinks the beneficial effect of a mutation is constrained by its "size" relative to the total size of the genome - the bigger the genome, the smaller the effect of a single mutation.   Assuming you and I are not misinterpreting, I think there are two possibilities: (a) - he really is that dumb (perhaps he thinks giraffes have more neck genes than humans); (b) - this is yet another silly exercise in apologetics - slosh a lot of sciency talk around, but fix it to make sure you get the answer Jesus wants you to get. I'm strongly leaning (b). -------------- Math is just a language of reality. Its a waste of time to know it. - Robert Byers There isn't any probability that the letter d is in the word "mathematics"...  The correct answer would be "not even 0" - JoeG

AnsgarSeraph Posts: 11 Joined: June 2009 (Permalink) Posted: June 16 2009,17:01    Quote (sledgehammer @ June 16 2009,14:42) Maybe someone who has MA up and running (Zach, Sam?) could try this and report? I was actually running simulations on this idea earlier today and will be posting some graphs up on TWeb within the next hour. The runs were identical, save that one run had a "maximal fitness effect" of 0.001 and the other a maximal fitness effect of 0.01. The first population, after ~6000 generations, had a fitness of 0.844. The second, after the same number of generations, had a fitness of 1.350. The number of beneficial mutations was cranked up to 75% to ensure the runs went for a significant number of generations. I also received an e-mail from Dr. Sanford today, part of which dealt in this area . . . I am waiting to hear from him whether I have permission to forward his entire e-mail on forums; there wasn't any revelatory information, in any case. Dr. Sanford feels that 0.001 is an appropriate setting but is willing to discuss whether that is the case or not. —Sam

sledgehammer Posts: 533 Joined: Sep. 2008 (Permalink) Posted: June 16 2009,17:46    Thanks Sam. Overall fitness switching from a negative trend to positive as a result of a 10X increase in "maximal beneficial fitness" seems to confirm that it is one of the most important parameters as far as the trend is concerned. Unfortunately, I can't see the attachments you posted on TWeb without registering.  Any chance you could post them here as well?  (Post them to my photobucket page, and then link them here via the image tag) -------------- The majority of the stupid is invincible and guaranteed for all time. The terror of their tyranny is alleviated by their lack of consistency. -A. Einstein  (H/T, JAD) If evolution is true, you could not know that it's true because your brain is nothing but chemicals. ?Think about that. -K. Hovind

Steve Schaffner Posts: 13 Joined: June 2009 (Permalink) Posted: June 16 2009,18:54    Quote (Zachriel @ June 14 2009,08:47) If the genome is 3e8 bases in size (or any such large number) and there is an average of one mutation per child, then we expect that ~1/3 of the children will *not* have mutations. If each mother produces 6 children, then chances are that each new generation will include many individuals without mutations. (E.g. mice often have several litters of 4-10 pups.) True, although that's probably not a good model for humans, who have something between 1 and 3 deleterious mutations (probably) per birth, and more likely close to the top end than the bottom of the range. That doesn't mean that the population has to collapse genetically. It just means that in the steady state, everyone is carrying a fair number of deleterious mutations, with those having the most being the least likely to reproduce. Quote If we use truncated selection, heritability=1, mutations=1, seed=30, all else default, this is what we see. Note that the population survives only because of truncation selection, which is not a realistic process for such slightly deleterious mutations. In this model, each individual will have on average one new mutation with a negative selection coefficient of something like 10-6 or 10-7, but selection is nonetheless effective enough to perfectly sort the fitness of the individuals and eliminate only the least fit. Quote It's interesting to see how the deleterious mutations ride along with the beneficial mutations until fixation before being weeded out. Yes. Selective sweeps in action.

AnsgarSeraph Posts: 11 Joined: June 2009 (Permalink) Posted: June 16 2009,19:00    I didn't see an option for me to add to your Photobucket page, so I registered and created my own. Here are the files. The first two are fitness graphs: These are the distribution graphs for JSW507 (deleterious first, beneficial second): And 508: I've uploaded all the pictures, as well as the Input and Output files to my Box.net account, also: MENDEL Run - JSW507, JSW508 —Sam

midwifetoad Posts: 4003 Joined: Mar. 2008 (Permalink) Posted: June 16 2009,19:12    Quote It just means that in the steady state, everyone is carrying a fair number of deleterious mutations, with those having the most being the least likely to reproduce. I'm having trouble coming to grips with the simple-mindedness of assuming that beneficial or deleterious mutations have any necessary effect at on on fecundity. My family hosts a number of odd and relatively undesirable alleles. We tend to have extra sets of front teeth -- which requires surgery to prevent blocking permanent teeth. My son has Adam's missing rib, something that gets painful when playing racket sports. Most of us are nearsighted. What we don't have are genes leading to early death or to belief in cult science. And based on anecdotal evidence, the inability to understand cumulative selection is positively correlated withing having nine children. -------------- Any version of ID consistent with all the evidence is indistinguishable from evolution.

Zachriel Posts: 2723 Joined: Sep. 2006 (Permalink) Posted: June 16 2009,19:38    Quote (Steve Schaffner @ June 16 2009,18:54)   Quote (Zachriel @ June 14 2009,08:47) If the genome is 3e8 bases in size (or any such large number) and there is an average of one mutation per child, then we expect that ~1/3 of the children will *not* have mutations. If each mother produces 6 children, then chances are that each new generation will include many individuals without mutations. (E.g. mice often have several litters of 4-10 pups.) True, although that's probably not a good model for humans, who have something between 1 and 3 deleterious mutations (probably) per birth, and more likely close to the top end than the bottom of the range. That doesn't mean that the population has to collapse genetically. It just means that in the steady state, everyone is carrying a fair number of deleterious mutations, with those having the most being the least likely to reproduce. It's probably not a good model for mice either. I'm trying a wide variety of parameters to determine the program's limits—or to break it. I've tried very high fecundity, high beneficial mutation rates, and various other extremes. What about additive vs. multiplicative mutational effects? Quote (AnsgarSeraph @ June 16 2009,19:00) Here are the files. The first two are fitness graphs: Is that with maximum beneficial effect equal to one versus default? Fraction favorable is set very high. Consider this. If we use the defaults, then no beneficial mutation becomes fixed, which is contrary to fact. Even if you believe species are ultimately doomed to genetic meltdown, it still means the default parameters or the program itself has a problem. -------------- You never step on the same tard twice—for it's not the same tard and you're not the same person.

AnsgarSeraph Posts: 11 Joined: June 2009 (Permalink) Posted: June 16 2009,19:51    Quote (Zachriel @ June 16 2009,19:38) Is that with maximum beneficial effect equal to one versus default? Fraction favorable is set very high. Consider this. If we use the defaults, then no beneficial mutation becomes fixed, which is contrary to fact. Even if you believe species are ultimately doomed to genetic meltdown, it still means the default parameters or the program itself has a problem. The first run (JSW507) has a maximum beneficial effect of 0.01, while the second run (JSW508) is set to the default 0.001. There's only one order of magnitude between the two runs. Sanford seems to be willing to give on the accuracy of the default parameters for the program . . . which is odd, in that those are the parameters he defends as biologically realistic in his papers. I think there are enough wrong parameters (and possibly a completely wrong coding paradigm) that any couple of parameters could be fixed and the population would still show fitness decline. At the moment, I'm leaning toward the idea that the program is broken . . . but hopefully we can get Dr. Sanford on TWeb soon enough and have some clear back-n-forth. —Sam

Zachriel Posts: 2723 Joined: Sep. 2006 (Permalink) Posted: June 16 2009,21:15    Quote (AnsgarSeraph @ June 16 2009,19:51) At the moment, I'm leaning toward the idea that the program is broken . . . but hopefully we can get Dr. Sanford on TWeb soon enough and have some clear back-n-forth. —Sam Every time they add a feature it seems to overlap another feature and reduce the effect of selection. "Probability selection" interacts with "Heritability". "Fraction of mutations beneficial" interacts with "maximum beneficial effect". How does Mendel's Accountant handle "probability selection". If they use Roulette Wheel selection, then it seems to negate the number of offspring setting. Nor does Roulette Wheel selection have a problem maintaining the population as suggested in the manual. I took a look at the source code, but it doesn't seem formatted for readability. -------------- You never step on the same tard twice—for it's not the same tard and you're not the same person.

mammuthus Posts: 13 Joined: June 2009 (Permalink) Posted: June 17 2009,14:12    The latest update is that Sanford will be engaged in a one on one discussion at TWeb with Steve Schaffner: Quote All right; I just finished responding back to Dr. Sanford. He appears to be willing to engage sfs1 in a discussion on TWeb. He agrees that a one-on-one discussion is best, since he prefers to keep the discussion from being polarized. I told Dr. Sanford that I would initiate the process of setting up a Basketball Court thread but I'm not sure how to do that; any long-timers here know how that works? We could use this thread as a commentary thread, I think. This has the potential to be really interesting. Dr. Sanford seems to be very genuine and polite; I think we've got a good chance to sort out some of MENDEL's problems without getting lost in the weeds. Dr. Sanford permitted me to post our e-mail exchange; the emails are attached. This is the part that concerns MENDEL: Quote As you know, Mendel has enormous user-specificity. It is literally a genetic accounting program, and honestly takes the input parameters which the users chooses, and processes them through the biological mechanics of mutation, selection, meiosis, gamete fusion, and formation of the next generation.    The default settings are just a starting point for research. If you put in the right parameters you can get extreme evolution. However, we argue that realistic settings always yield degeneration. This can be a point of discussion.    In regrad to your own experiments, I would like to point out that    biologists realize that the distribution of good and bad mutations are not symetrical. There are far fewer beneficials, and the range of beneficials is different - it is generally acknowledged that beneficials have a lower mean effect (is is harder to make major improvements in a highly optimized system). If you go to the mutation specifications, you can specify a high maximal beneficial effect - even up to 1.0. The default is .001 - meaning that a maximal beneficial effect is small, increasing fitness by 0.1%. A setting of 1.0 means that a single mutation can double fitness - creating as much biological functionality as the entire rest of the genome. This type of setting has many biological and logical ramifications that require quite a bit of discussion. In an accounting program, a single mega-beneficial can ALWAYS compensate for any amount of genetic damage. But is that realistic? A big thanks to sfs1 for agreeing to dialog with Dr. Sanford when he comes to TWeb. This should be an illuminating discussion and a great addition to the stuff we've already figured out. —Sam I think you'll have to register at TWeb to view the debate when it comes up online.

Zachriel Posts: 2723 Joined: Sep. 2006 (Permalink) Posted: June 17 2009,15:11    Quote (JohnW @ June 16 2009,15:47)   Quote (sledgehammer @ June 16 2009,12:42) I think it is even worse that that Zach, for three reasons: <snip> I think you're right, sledgehammer.  It looks like Sanford thinks the beneficial effect of a mutation is constrained by its "size" relative to the total size of the genome - the bigger the genome, the smaller the effect of a single mutation.   Assuming you and I are not misinterpreting, I think there are two possibilities: (a) - he really is that dumb (perhaps he thinks giraffes have more neck genes than humans); (b) - this is yet another silly exercise in apologetics - slosh a lot of sciency talk around, but fix it to make sure you get the answer Jesus wants you to get. I'm strongly leaning (b). He just said it again. Quote Sanford: A setting of 1.0 means that a single mutation can double fitness - creating as much biological functionality as the entire rest of the genome. A doubling in fitness does not imply a doubling of "biological functionality". Resistance to plague doesn't imply a dramatic increase in the size of a genome. It may just mean that fleas think you smell bad. -------------- You never step on the same tard twice—for it's not the same tard and you're not the same person.

sledgehammer Posts: 533 Joined: Sep. 2008 (Permalink) Posted: June 17 2009,16:39    Quote Sanford: A setting of 1.0 means that a single mutation can double fitness - creating as much biological functionality as the entire rest of the genome. I don't buy that argument either. This is from: J. Sanford, J. Baumgardner, W. Brewer, P. Gibson, and W. Remine. Mendel's Accountant: A biologically realistic forward-time population genetics program. SCPE. 8(2), July 2007, pp. 147-165.         Quote 3.2. Prescribing Fitness Effects of Mutations. ...These scale factors are meaningful relative to the initial fitness value assumed for the population before we introduce new mutations. In Mendel we assume this initial fitness value to be 1.0. For deleterious mutations, since lethal mutations exist, we choose dsf del = -1. For favorable mutations, we allow the user to specify the (positive) scale factor dsf fav. Normally, this would be a small value (e.g., 0.01 to 0.1), since it is only in very special situations that a single beneficial mutation would have a very large effect. Seems to me that if the scale factor for deleterious mutations of -1 represents lethality, (i.e. no chance of reproduction), then it's inverse for beneficial mutations, +1, would represent guaranteed reproductive success, not "doubling of fitness". -------------- The majority of the stupid is invincible and guaranteed for all time. The terror of their tyranny is alleviated by their lack of consistency. -A. Einstein  (H/T, JAD) If evolution is true, you could not know that it's true because your brain is nothing but chemicals. ?Think about that. -K. Hovind

Zachriel Posts: 2723 Joined: Sep. 2006 (Permalink) Posted: June 17 2009,19:39    Quote (sledgehammer @ June 17 2009,16:39)     Quote Sanford: A setting of 1.0 means that a single mutation can double fitness - creating as much biological functionality as the entire rest of the genome. I don't buy that argument either. This is from: J. Sanford, J. Baumgardner, W. Brewer, P. Gibson, and W. Remine. Mendel's Accountant: A biologically realistic forward-time population genetics program. SCPE. 8(2), July 2007, pp. 147-165.               Quote 3.2. Prescribing Fitness Effects of Mutations. ...These scale factors are meaningful relative to the initial fitness value assumed for the population before we introduce new mutations. In Mendel we assume this initial fitness value to be 1.0. For deleterious mutations, since lethal mutations exist, we choose dsf del = -1. For favorable mutations, we allow the user to specify the (positive) scale factor dsf fav. Normally, this would be a small value (e.g., 0.01 to 0.1), since it is only in very special situations that a single beneficial mutation would have a very large effect. Seems to me that if the scale factor for deleterious mutations of -1 represents lethality, (i.e. no chance of reproduction), then it's inverse for beneficial mutations, +1, would represent guaranteed reproductive success, not "doubling of fitness". Relative fitness compares different genotypes in a population, and is defined as the ratio of the average numbers contributed to the next generation with one genotype set arbitarily at 1. So if genotype-A contributes 300 and normal genotype-B contributes 200, then genotype-A has a relative fitness of 1.5 compared to genotype-B. Relative fitness can be most any non-negative number. Absolute fitness is calculated for a single genotype as simply the ratio of the numbers in the new generation to the old after selection. So if the population of the genotype increases from 100 to 200, then it has an absolute fitness of 2. Again, absolute fitness can be most any non-negative number. I've been trying to independently implement Mendel's Accountant, but keep running into such definitional problems. Heritability. Fitness. And how they're handling probability selection. I'm working with a simplified model, but Mendel's Accountant should be able to handle the simple cases with obvious results. I'm assuming that if fitness increases by 1, then it goes from 1 to 2 (100% increase), or from 2 to 3 (50%) and so on. It shouldn't be additive, but multiplicative so it scales. Sanford's complaint is that if we use multiplicative, then it can never reach zero. So he is clearly assuming his conclusion. It's not easy to resolve some of these problems. If we scale fecundity with fitness, then that solves the problem of very low fitness. But introduces a problem if the fitness levels climb so that we may be radically multiplying the reproductive rate. Of course, "generation" is an abstraction, so it may represent an undefined breeding season. Frankly, the whole thing is an abstraction, so any strong claims about the specifics of biology are invalid anyway. -------------- You never step on the same tard twice—for it's not the same tard and you're not the same person.

Henry J Posts: 5787 Joined: Mar. 2005 (Permalink) Posted: June 17 2009,20:19    Quote I took a look at the source code, but it doesn't seem formatted for readability. Maybe it evolved? Henry

Zachriel Posts: 2723 Joined: Sep. 2006 (Permalink) Posted: June 17 2009,20:59    Some bits from Mendel's Accountant source code. Offspring: if(fitness_dependent_fertility) then               fitness_adjusted_offspring = num_offspring*sqrt(post_sel_fitness) Favorable Mutations: c...  Compute mean absolute fitness effect for favorable mutations.      sum = 0.      d2  = 1.      do i=1,1000000         d1 = d2         d2 = exp(-alpha_fav*(0.000001*i)**gamma_fav)         sum = sum + d1 + d2      end do      fav_mean = 0.0000005*sum*max_fav_fitness_gain Phenotypic Fitness:      noise = sqrt(geno_fitness_variance*(1. - heritability) /heritability + non_scaling_noise**2) c...  Add noise to the fitness to create a phenotypic fitness score... do i=1,total_offspring         pheno_fitness(i) = fitness(i) + random_normal()*noise Unrestricted probability selection: c...     For unrestricted probability selection, divide the phenotypic   c...     fitness by a uniformly distributed random number prior to c...     ranking and truncation.  This procedure allows the probability c...     of surviving and reproducing in the next generation to be c...     directly related to phenotypic fitness and also for the correct c...     number of individuals to be eliminated to maintain a constant c...     population size.         do i=1,total_offspring            work_fitness(i) = work_fitness(i)/(randomnum(1) + 1.d-15)         end do Divide by randomnum as well as add non-heritable noise to the phenotype? -------------- You never step on the same tard twice—for it's not the same tard and you're not the same person.

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