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version 3.3

Windows 7/8/10 (64-bit OS required) or Mac OS X 10, 3 GB RAM, graphics card equivalent to ATI Radeon 5570 or NVIDIA GeForce 430 GT with 1 GB memory, approx. 1,5 GB HDD space. We also highly recommend to use a gamepad (Xbox 360/One Controller or PS 3/4 Controller) to play NIVA.

October, 2008

This is a one-locus, two-allele genetic simulation program for use bystudents. Earlier versions were called Simul8.At our distribution serverevolution.gs.washington.edu in folder pub/popgenthere are archives that can be fetched for Windows, Mac OS, Mac OS X and Linux.These contain executables and documentation. A source code archive isalso available there which has support files for compiling your own versionof the program in these operating systems. Normally you will not need thesource code and you will not need to recompile the program. The source codecan also be used to make versions for other varieties of Unix.See below for links that will enable you to fetch the archives.

Getting PopG

You can fetch PopG using the links below.

• For Windows: popgwin.exeA self-extracting zip archive containing the files of the Windows versionfor Windows 95, 98, NT, 2000, me, xp, Vista and as far as weknow all other recent versions of windows.
• For Mac OS X: popgosx.dmgA Mac OS X version which can be run on any version of Mac OS X as aUniversal native-mode executable. It is a .dmg 'disk image' file.
• For Linux: popglinux.tar.gz Linux version, as a Gnuzip'ed tar archive ofthe executables and documentation.

There are also executable versions for some older kinds of computers, includingearlier Unix workstations, pre-Windows DOS systems, and earlier Macintoshprocessors. These can be fetched from folder old at our PopG site. Most users will not need touse these older executables, but if you do, you should start by reading theREADME file in that folder.

The documentation

The documentation files are included in the fetchable archives, and consistof this web page. The latest version of it can be read on the Webusing this link.

Unpacking the archives

After fetching the archives for Windows, for Mac, or for Linux/Unix, you needto unpack them. Do this:

For Windows

Make sure the popgwin.exe file is in the folder where you wantthe program to be. The click on it. It will run and unpack itself intoa set of files, including this documentation file and thePopG executable. These will be in a folder (directory) called PopG_3.3

For Mac OS X

After the disk image has been downloaded, you should click on it tomount it. A new folder should open showing the contents of the disk image.It will have a folder (directory) PopG_3.3 withdocumentation, an icon graphic, and thePopG executable). Copy the PopG_3.3 folder to some otherplace on your system, outside of the disk image (such as your desktop). Donot try to use it inside the disk image.

For Linux or Unix

Put the popglinux.tar.gz file into the folder where you wantthe program to reside and dotar xvfz popglinux.tar.gz. This will create afolder (directory) called PopG_3.3 that contains these files.

Running the program

To run the program on Linux or Unix systems you should simply type popgwhile in the proper directory.On Windows or Macintosh systems you simply click (or double-click) on theprogram icon.

The program uses a random number generator. It should give you a different result every time it is run.

The program opens a window, and there are three menus that you can use tocontrol it. On Windows and Linux/Unix systems the menus are in the upperleft of the main window. On Mac OS they are in the upper left of yourdesktop window. The windows are File and Run. Most of their menu itemscan selected using the mouse or else (in the Windows and Macintosh cases) bytyping the appropriate character on the keyboard. On Windows systemsthese are Control characters such as Control-C (holding down theCtrl key while typing C). On Macintosh systems they areCommand characters such as Command-C (holding down the Command key while typing C.

The Run menu

This contains four menu items, Continue w/, Continue, New Run, and Restart.

New Run (Control-N or Command-N)

Initially only New Run is available. It brings up a box withparameter values that can be changed, marking then with the mouse and usingbackspace and/or delete keys, and typing modified values in. When these aregiven the desired values, clicking the OK box will dismiss theparameter values and start the run. If at any point you want to restartthe run with different parameter values, you can select New Runand you will be given a chance to change the parameters.

Continue w/ (Control-C or Command-C)

This choice continues the run, for the same number of generations asbefore (which is shown in the menu).

Continue

This continues the run, but presents a box allowing the user to firstchange the number of generations run in the continuation of the run.

Restart (Control-R or Command-R)

This restarts the run with the same parameter values as before. If youwant to change some of the parameter values, use New Run instead.

The File menu

This contains four menu items, which may not all be available. They areSave, Print, About and Quit.

Quit (Control-Q or Command-Q)

This is self-explanatory: the program quits.

Print (Control-P or Command-P)

This sends the present image of the graph to the system's print queue.On Windows, Mac OS X or Mac OS 9 systems it will present the user with a'print box'in which various options can be selected. On Linux or Unix systems it willsend the graph as a Postscript file to the system's lprprinting command.

Save (Control-S or Command-S)

This saves the graph as a Postscript file, allowing the user toselect the name of the file (the default name is output.ps).

About (Control-A or Command-A)

Displays the program's copyright notice.

Compiling it yourself

Most people will not have to compile the program themselves, and thus theywon't need a C compiler for it. But if you want to modify the program, orif you want to port it to a different version of Unix, you will need tocompile the program. If you don't need to do any of these, you can just usethe executables that we distribute.

If you do need to compile the program, first download from our site theappropriate source code archive, and make sure it is extracted into a folder.Instructions for downloading and compiling the source code are availableon our server, where you will finda web pagewith those instructions.There are downloadable files that contain source code, compilinginstructions, and compilation support files for Windows, for Linux and Unixsystems, and for Mac OS 9 and Mac OS X systems. After you download the correctsource code archive, use your browser to read the compiling.htmlweb page in the main source code folder. It contains instructions forcompiling in each of these operating systems.

Simulating with PopG

This program simulates the evolution of random-mating populations with two alleles, arbitrary fitnesses of the three genotypes, an arbitrary mutation rate, an arbitrary rate of migration between the replicate populations, andfinite population size.

The programs simulate ten simultaneously evolving populations with youspecifying the population size, the fitnessesof the three genotypes, the mutation rates in both directions (from A to aand from a to A), and the initial gene frequency. They also ask for amigration rate among all the populations, which will make their genefrequencies more similar to each other. Much of the time (but not always!)you will want to set this migration rate to zero. In most respects theprogram is self-explanatory.

When you make a menu selection that causes the program to run,a graph of the gene frequencies of the A allele in each of thepopulations will be drawn in the window. Note that the window can beresized, and the graph should adjust to this. There will also be a dashed curve that shows what thegene frequencies would be in an infinite population (one with nogenetic drift). The graph can be printed using the Printoption of the File menu, or saved to a Postscript file usingthe Save option in that menu.

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Note that once the plot of the gene frequency curves reaches theright-hand side of the graph, the program prints there the number ofpopulations that fixed for the A allele (ended up with afrequency of 1.0) and the number that lost this allele.

The program can simulate a wide variety of cases, and you shouldexplore some of these. Here are some suggestions:

• Try cases with no mutation, no migration, and all fitnesses 1.0 sothat there is no selection. Does genetic drift in a population ofsize 1000 accomplish roughly the same changes in 1000 generations asgenetic drift in a population of size 100 does in 100 generations?By running a largish number of populations, can you check whetherthe probability that an allele is fixed by genetic drift is equal toits initial frequency in the populations?
• Try a case with no mutation or migration, with the Aallele favored by natural selection (with fitness of the AAgenotype set highest and fitness of the aa genotype setlowest). Start with a small frequency of A. Is it alwaysfixed? If one starts with a single copy of the allele, how doesthe probability that A is fixed compare with the selectioncoefficient favoring it in the heterozygote (compared to the fitnessof the aa genotype? Is this fixation probability larger thanthe one you would get with the same initial frequency with noselection?
• Try overdominance (Aa having the highest fitness). Doesthe gene frequency converge towards an equilibrium? Why does itvary from this equilibrium frequency? How large do the selectioncoefficients have to be to cause the gene frequency to stay away fromfixation or loss for large amounts of time?
• Try underdominance (Aa having the lowest fitness).Is there a starting gene frequency that will result in some populationsheading for fixation, and others heading for loss? If you add a smallamount of migration, what will happen? if you add a small amount ofmutation in both directions?
• With migration but no selection or mutation, how much migration isneeded to make the gene frequency curves be quite similar to each other?How much is needed to make them all end up at the same gene frequency?How is that migration rate affected by the population size?
• With mutation but no migration or selection, how much mutation isneeded to cause the gene frequencies to converge on a mutationalequilibrium gene frequency? How does this value relate to thepopulation size?
• If an allele is selected against, can you set up mutation ratesthat will maintain it at low frequency in the population?

You should be able to use the program to get a good feel for the relative strengths of different evolutionary forces. It is worthwhiletrying many different kinds of cases and asking what values ofparameters are needed to make one evolutionary force be influential inthe presence of another.

Credits

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PopG was written by Joe Felsenstein, Hisashi Horino, Sean Lamont,Bill Alford, Mark Wells, Mike Palczewski, Doug Buxton, and ElizabethWalkup. I wrote the originalversion of the program. Hisashi and Sean did the screen graphics forIBM PC and the first part of the Postscript printing system. Billgreatly improved and expanded the Postscript printing andthe X windows graphics. Mark Wells did theoriginal Macintosh version. Mike Palczewski greatly improved the Windows,Macintosh and X Windows graphical user interface, and Doug Buxton modified theprogram to the 3.0 version and prepared the executables for differentoperating systems. Elizabeth Walkup improved the X windows interactionand prepared version 3.3.

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Copyright notice

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Copyright 1993-2008. University of Washington and Joseph Felsenstein. Allrights reserved. Permission is granted to reproduce, perform, and modifythis program. Permission is granted to distribute or provide access to thisprogram provided that this copyright notice is not removed, this program isnot integrated with or called by any product or service that generatesrevenue, and that your distribution of this program is free. Any modifiedversions of this program that are distributed or accessible shall indicatethat they are based on this program. Educational institutions aregranted permission to distribute this program to their students and stafffor a fee to recover distribution costs. Permission requests for any otherdistribution of this program should be directed to license @ u.washington.edu.

Joe Felsenstein Department of Genome Sciences University of Washington Box 355065 Seattle, WA 98195-5065, USA

email: joe @ gs.washington.edu