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+ | {{: | ||
+ | |||
+ | ======== | ||
+ | |||
+ | ---- | ||
+ | |||
+ | This page contains links to various software resources associated with active and previous research projects performed with my colleagues. | ||
+ | |||
+ | =====neqPopDynx===== | ||
+ | |||
+ | ---- | ||
+ | |||
+ | //**This is work in progress, so please use with caution!!**. | ||
+ | |||
+ | **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 // | ||
+ | |||
+ | Files for neqPopDynx_v1.5: | ||
+ | * Python 3 script: {{neqPopDynx_v1.5.0.py.zip}} | ||
+ | * Example bash scripts for equilibrium, | ||
+ | |||
+ | //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===== | ||
+ | ---- | ||
+ | Written by Daniel J. Balick | ||
+ | |||
+ | //For citations, please reference our [[https:// | ||
+ | |||
+ | **simDoSe** (__Sim__ulate __Do__minance and __Se__lection) is a fast Wright-Fisher simulator for arbitrary diploid selection evolving through realistic human demography. | ||
+ | |||
+ | ====Features==== | ||
+ | * Produces a simulated site frequency spectrum (SFS) and summary statistics for user specified demography and diploid selection. | ||
+ | * Models random sampling of a population to output the SFS of a sequenced population sample with user specified sample size. | ||
+ | * Option to create many simulated ' | ||
+ | * Option to create gene sets from an imported list of lengths (i.e., target size/ | ||
+ | * Option to simultaneously create ' | ||
+ | * Fast and flexible due to the absence of linkage (i.e., infinite recombination limit) | ||
+ | * Arbitrary dominance and selection coefficients, | ||
+ | * Properly handles high mutation rates with a command-line option for the recurrent mutation kernel. | ||
+ | * Choose from several literature-based demographies, | ||
+ | * Can model ' | ||
+ | * Entirely command line-based, so the only needed software is Python 2.7 and the numpy, scipy, and pandas packages. | ||
+ | * Flexible output specification, | ||
+ | |||
+ | ====Additional details, instructions for running, examples==== | ||
+ | Please see the simDoSe [[https:// | ||
+ | |||
+ | ====Downloading simDoSe==== | ||
+ | simDoSe is available for [[https:// | ||
+ | |||
+ | =====srMLgenes===== | ||
+ | ---- | ||
+ | Written by Daniel M. Jordan\\ | ||
+ | //For citations, please reference our [[https:// | ||
+ | |||
+ | |||
+ | **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). | ||
+ | |||
+ | ====Features==== | ||
+ | |||
+ | * Users can view the histogram of the maximum likelihood diploid selection coefficients for a human gene set in the the plane of dominance (h) and selection (s) coefficients. | ||
+ | * Users can view the odds ratio and p-values of the computed enrichment/ | ||
+ | * Toggle between (h,s) view and bar plots depicting enrichment for strong recessive and strong additive selection, the primary focus of our comparative analyses. | ||
+ | * Inference was performed using Exome Aggregation Consortium (ExAC) data from the non-Finnish European (NFE) cohort. | ||
+ | * Maximum likelihood values were obtained using simulations performed with [[https:// | ||
+ | * Users can explore both ExAC data and simulated gene sets in comparison to simulated genomic backgrounds. | ||
+ | * Gene sets can be restricted to an arbitrary mutational target size (i.e., gene length) range to remove spurious effects from short genes with low confidence inferences | ||
+ | |||
+ | ====Web link and Download details==== | ||
+ | |||
+ | The web-based version of srMLgenes is available [[http:// | ||
+ | |||
+ | ===== Mutational Burden Simulator ===== | ||
+ | |||
+ | ---- | ||
+ | Written by David Reich | ||
+ | |||
+ | //For citations, please reference our [[http:// | ||
+ | |||
+ | ==== Simulating selection and dominance in a non-equilibrium demography ==== | ||
+ | |||
+ | How does a population bottleneck impact the mutation burden under differing dominance and selection coefficients? | ||
+ | |||
+ | Below is the code for **burden_sim**, | ||
+ | |||
+ | ====Files for burden_sim==== | ||
+ | |||
+ | * Readme file: {{README_burden_sim_v0.pdf|README}} | ||
+ | * Simulation Code (written in C) {{burden_sim_code.zip}} | ||
+ | * Compiled code: | ||
+ | * Burden simulation for simple (square) bottleneck: | ||
+ | * Burden simulation for Gravel demography: | ||
+ | * Burden simulation for Tennessen demography: | ||
+ | |||
+ | ---- | ||
+ | |||
+ | //This page is managed by DJB and does not necessarily reflect the Sunyaev lab as a whole.// | ||