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dbalick [2023/01/09 15:05] – [neqPopDynx] ivandbalick [2023/01/09 15:48] (current) – ivan
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 ========  Daniel J. Balick's Software and Resources ======== ========  Daniel J. Balick's Software and Resources ========
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 This page contains links to various software resources associated with active and previous research projects performed with my colleagues.  Feel free to email [[dbalick@hms.harvard.edu]] or [[dbalick@gmail.com]] if you have any questions, comments, or suggestions. This page contains links to various software resources associated with active and previous research projects performed with my colleagues.  Feel free to email [[dbalick@hms.harvard.edu]] or [[dbalick@gmail.com]] if you have any questions, comments, or suggestions.
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 =====neqPopDynx===== =====neqPopDynx=====
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-//**This is work in progress, so please use with caution!!**.  I will be updating this (with any bug fixes) as needed. //+//**This is work in progress, so please use with caution!!**.  I will be updating this (with any bug fixes) as needed.//
  
 **neqPopDynx** (__N__on-__eq__uilibrium __Pop__ulation __Dyn__ami__x__) is a flexible, terminal-based Wright-Fisher simulator scripted in Python 3 for outputting temporal data.  Allele frequencies evolve independently in the infinite recombination limit to assess properties of the allele frequency //probability distribution// and are subject to user-specified rates of mutation and back mutation rates (allowing for recurrence), selection and dominance coefficients, initial population size, and a choice of pre-specified demographic changes in the population size with specifiable parameters (e.g., growth rate of exponential expansion, bottleneck start time, duration, and diploid size).  The purpose of this simulator is to produce robust temporal output of the non-central moments, central moments, and/or cumulants of the allele frequency probability distribution averaged over L independent sites starting from the same initial frequency p_0=n/2N.  This allows for comparison to analytic results of the equilibration process towards mutation-selection-drift balance and the dynamics of fully non-equilibrium demographic scenarios (e.g., exponential growth, population bottlenecks).  **neqPopDynx** (__N__on-__eq__uilibrium __Pop__ulation __Dyn__ami__x__) is a flexible, terminal-based Wright-Fisher simulator scripted in Python 3 for outputting temporal data.  Allele frequencies evolve independently in the infinite recombination limit to assess properties of the allele frequency //probability distribution// and are subject to user-specified rates of mutation and back mutation rates (allowing for recurrence), selection and dominance coefficients, initial population size, and a choice of pre-specified demographic changes in the population size with specifiable parameters (e.g., growth rate of exponential expansion, bottleneck start time, duration, and diploid size).  The purpose of this simulator is to produce robust temporal output of the non-central moments, central moments, and/or cumulants of the allele frequency probability distribution averaged over L independent sites starting from the same initial frequency p_0=n/2N.  This allows for comparison to analytic results of the equilibration process towards mutation-selection-drift balance and the dynamics of fully non-equilibrium demographic scenarios (e.g., exponential growth, population bottlenecks). 
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 Files for neqPopDynx_v1.5: Files for neqPopDynx_v1.5:
   * Python 3 script: {{neqPopDynx_v1.5.0.py.zip}}    * Python 3 script: {{neqPopDynx_v1.5.0.py.zip}} 
-  * Example bash scripts for equilibrium, exponential, bottleneck, and oscillatory demographies: {{ :bash_scripts_to_run_neqPopDynx_v1.5.zip |}}+  * Example bash scripts for equilibrium, exponential, bottleneck, and oscillatory demographies: {{bash_scripts_to_run_neqPopDynx_v1.5.zip}}
  
 //Note: As this is work in progress, if you do happen to use this simulator, please provide any feedback you have via email to// [[dbalick@hms.harvard.edu|dbalick@hms.harvard.edu]] or [[dbalick@gmail.com|dbalick@gmail.com]]. //Note: As this is work in progress, if you do happen to use this simulator, please provide any feedback you have via email to// [[dbalick@hms.harvard.edu|dbalick@hms.harvard.edu]] or [[dbalick@gmail.com|dbalick@gmail.com]].
 =====simDoSe===== =====simDoSe=====
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-Written by Daniel J. Balick \\ +Written by Daniel J. Balick 
-//For citations, please reference our [[https://doi.org/10.1016/j.ajhg.2021.12.001|American Journal of Human Genetics]] manuscript. + 
-//+//For citations, please reference our [[https://doi.org/10.1016/j.ajhg.2021.12.001|American Journal of Human Genetics]] manuscript.//
  
 **simDoSe** (__Sim__ulate __Do__minance and __Se__lection) is a fast Wright-Fisher simulator for arbitrary diploid selection evolving through realistic human demography.  **simDoSe** (__Sim__ulate __Do__minance and __Se__lection) is a fast Wright-Fisher simulator for arbitrary diploid selection evolving through realistic human demography. 
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 ====Features==== ====Features====
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   * Entirely command line-based, so the only needed software is Python 2.7 and the numpy, scipy, and pandas packages.   * Entirely command line-based, so the only needed software is Python 2.7 and the numpy, scipy, and pandas packages.
   * Flexible output specification, including full population, population sample, and per-gene site frequency spectra and corresponding summary statistics   * Flexible output specification, including full population, population sample, and per-gene site frequency spectra and corresponding summary statistics
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 ====Additional details, instructions for running, examples==== ====Additional details, instructions for running, examples====
 Please see the simDoSe [[https://github.com/dbalick/simDoSe/blob/main/simDoSe_user_manual.pdf|User Manual]] for detailed information on the mathematical models and commannd line options. Please see the simDoSe [[https://github.com/dbalick/simDoSe/blob/main/simDoSe_user_manual.pdf|User Manual]] for detailed information on the mathematical models and commannd line options.
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 ====Downloading simDoSe==== ====Downloading simDoSe====
 simDoSe is available for [[https://github.com/dbalick/simDoSe|download]] on GitHub, where you can find the Python 2.7 script for the latest version, the relevant Anaconda environment shell script, and the [[https://github.com/dbalick/simDoSe/blob/main/simDoSe_user_manual.pdf|User Manual]] detailing instructions for using simDoSe. simDoSe is available for [[https://github.com/dbalick/simDoSe|download]] on GitHub, where you can find the Python 2.7 script for the latest version, the relevant Anaconda environment shell script, and the [[https://github.com/dbalick/simDoSe/blob/main/simDoSe_user_manual.pdf|User Manual]] detailing instructions for using simDoSe.
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 =====srMLgenes===== =====srMLgenes=====
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 **srMLgenes** is a web-based visualization tool to analyze the enrichment of pre-specified or user-uploaded gene sets for strong recessive purifying selection (or for strong additive selection, neutrality, and other diploid selection coefficients of interest).   **srMLgenes** is a web-based visualization tool to analyze the enrichment of pre-specified or user-uploaded gene sets for strong recessive purifying selection (or for strong additive selection, neutrality, and other diploid selection coefficients of interest).  
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 ====Features==== ====Features====
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 The web-based version of srMLgenes is available [[http://srmlgenes.herokuapp.com/|here]] and a script can be downloaded directly from GitHub [[https://github.com/rondolab/srmlgenes/|here]] to run srMLgenes on a local computer. The web-based version of srMLgenes is available [[http://srmlgenes.herokuapp.com/|here]] and a script can be downloaded directly from GitHub [[https://github.com/rondolab/srmlgenes/|here]] to run srMLgenes on a local computer.
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 =====  Mutational Burden Simulator ===== =====  Mutational Burden Simulator =====
  
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 +Written by David Reich
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 +//For citations, please reference our [[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005436|PLOS Genetics]] manuscript and our [[http://www.nature.com/ng/journal/v47/n2/abs/ng.3186.html|Nature Genetics]] manuscript.//
  
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-Written by David Reich\\ 
-//For citations, please reference our [[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005436|PLOS Genetics]] manuscript and our [[http://www.nature.com/ng/journal/v47/n2/abs/ng.3186.html|Nature Genetics]] manuscript. 
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 ==== Simulating selection and dominance in a non-equilibrium demography ==== ==== Simulating selection and dominance in a non-equilibrium demography ====
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 How does a population bottleneck impact the mutation burden under differing dominance and selection coefficients? How does a population bottleneck impact the mutation burden under differing dominance and selection coefficients?
  
 Below is the code for **burden_sim**, a simulation of the mutation burden for two populations after a split, as described in [[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005436|Balick et al]].    Below is the code for **burden_sim**, a simulation of the mutation burden for two populations after a split, as described in [[http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005436|Balick et al]].   
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 ====Files for burden_sim==== ====Files for burden_sim====
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       * Burden simulation for Gravel demography:  {{burden_sim_Gravel.zip}}       * Burden simulation for Gravel demography:  {{burden_sim_Gravel.zip}}
       * Burden simulation for Tennessen demography:  {{burden_sim_Tennessen.zip}}       * Burden simulation for Tennessen demography:  {{burden_sim_Tennessen.zip}}
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 //This page is managed by DJB and does not necessarily reflect the Sunyaev lab as a whole.//  //This page is managed by DJB and does not necessarily reflect the Sunyaev lab as a whole.//