{"id":32635225,"url":"https://github.com/kr-colab/discoal","last_synced_at":"2026-02-22T22:47:13.662Z","repository":{"id":33899115,"uuid":"37613630","full_name":"kr-colab/discoal","owner":"kr-colab","description":"discoal is a coalescent simulation program capable of simulating models with recombination, selective sweeps, and demographic changes including population splits, admixture events, and ancient 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Status](https://readthedocs.org/projects/discoal/badge/?version=latest)](https://discoal.readthedocs.io/en/latest/?badge=latest)\n\n# discoal\ndiscoal is a coalescent simulation program capable of simulating models with recombination, selective sweeps, and demographic changes including population splits and admixture events.\n\n**Recent improvements**: Memory optimizations have increased the maximum sample size from 254 to 65,535 samples, eliminated the need for the `-DBIG` compilation flag, and reduced memory usage by 15-99% across different simulation scenarios.\n\n## Documentation\n\nFull documentation is available at [https://discoal.readthedocs.io](https://discoal.readthedocs.io)\n\nThe documentation includes:\n- Installation instructions\n- Detailed usage guides and examples\n- Complete parameter reference\n- Advanced features and workflows\n\nA PDF version is also available in `discoaldoc.pdf`.\n\n## Quick Start\n\nTo install discoal, clone this repository, cd into the directory, then assuming you have gcc and make installed on your system, simply type `make discoal`.\n\nFor a quick reference, typing `./discoal` will bring up a verbose usage statement:\n```\n$ ./discoal\nusage: discoal sampleSize numReplicates nSites -ws tau\nparameters:\n\t -t theta\n\t -r rho (=zero if not specified)\n\t -g conversionRate tractLengthMean (gene conversion)\n\t -gr conversionToCrossoverRatio tractLengthMean (gene conversion where initiation rate = rho*conversionToCrossoverRatio)\n\t -p npops sampleSize1 sampleSize2 etc.\n\t -en time popnID size (changes size of popID)\n\t -ed time popnID1 popnID2 (joins popnID1 into popnID2)\n\t -ea time daughterPopnID founderPopnID1 founderPopnID2 admixProp (admixture-- back in time daughterPopnID into two founders)\n\t -ws tau (sweep happend tau generations ago- stochastic sweep)\n\t -wd tau (sweep happend tau generations ago- deterministic sweep)\n\t -wn tau (sweep happend tau generations ago- neutral sweep)\n\t -ls tau leftRho (stochastic sweep some genetic distance to the left of the simulated window--specified by leftRho=4Nr)\n\t\t similarly, ld and ln simulate deterministic and neutral sweeps to the left of the window, respectively\n\t -f first frequency at which selection acts on allele (F0; sweep models only)\n\t -uA rate at which adaptive mutation recurs during the sweep phase (sweep models only)\n\t -N sweepEffectivePopnSize (sweep models only)\n\t -a alpha (=2Ns)\n\t -x sweepSite (0-1)\n\t -c partialSweepFinalFrequency (partial sweeps)\n\t -i dt (sweep time increment scalar; default 400 -\u003e 1/400N)\n\t -M migRate (sets all rates to migRate)\n\t -m popnID1 popnID2 migRate (sets migRate from popnID1 to popnID2)\n\t -A sampleSize popnID time (ancient sample from popnID at specified time)\n\t -Pt low high (prior on theta)\n\t -Pr low high (prior on rho)\n\t -Pre mean upperBound (prior on rho -- exponentially distributed but truncated at an upper bound)\n\t -Pa low high (prior on alpha)\n\t -Pu low high (prior on tau; sweep models only; still must use \"-ws tau\" and \"tau\" will be ignored)\n\t -PuA low high (prior on uA; sweep models only)\n\t -Px low high (prior on sweepSite; sweep models only)\n\t -Pf low high (prior on F0; sweep models only)\n\t -Pc low high (prior on partialSweepFinalFreq; sweep models only)\n\t -Pe1 lowTime highTime lowSize highSize (priors on first demographic move time and size)\n\t -Pe2 lowTime highTime lowSize highSize (priors on second demographic move time and size)\n\t -R rhhRate (recurrent hitch hiking mode at the locus; rhh is rate per 2N individuals / generation)\n\t -L rhhRate (recurrent hitch hiking mode to the side of locus; leftRho is ~Unif(0,4Ns); rhh is rate per 2N individuals / generation)\n\t -h (hide selected SNP in partial sweep mode)\n\t -T (tree output mode)\n\t -d seed1 seed2 (set random number generator seeds)\n```\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkr-colab%2Fdiscoal","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkr-colab%2Fdiscoal","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkr-colab%2Fdiscoal/lists"}