Inferring long-term effective population size with Mutation-Selection models

All scripts, instructions and empirical datasets (alignments, trees, life-history traits, fossile calibrations) necessary to reproduce the simulated and empirical analyses are available in Github, at https://github.com/ThibaultLatrille/MutationSelectionDrift.<br> The Bayesian inference model, written in C++ in the component based software BayesCode, is available at https://github.com/ThibaultLatrille/bayescode.<br> The simulation software SimuEvol, written in C++ is available at https://github.com/ThibaultLatrille/SimuEvol. These empirical and simulated analyses can take several weeks to run, hence, this figshare repository contains the output of the inference model (BayesCode) and analyses on both simulated (SimuEvol) and empirical dataset. Usage Notes Clone (or download) the repository MutationSelectionDrift available at https://github.com/ThibaultLatrille/MutationSelectionDrift. <br> Extract the file 'DataSimulatedExperiments.tar.xz' into the folder 'DataSimulated'.<br>Extract the file 'DataEmpiricalExperiments.tar.xz' into the folder 'DataEmpirical'.<br>Extract the file 'DataEmpiricalAnalysis.tar.xz' into the subfolder 'Analysis' of folder 'DataEmpirical'.

所有用于复现模拟分析与实证分析的脚本、操作指南及实证数据集（含序列比对（alignments）、系统发育树（trees）、生活史特征（life-history traits）与化石校准（fossile calibrations）），均可从GitHub仓库https://github.com/ThibaultLatrille/MutationSelectionDrift获取。
采用C++语言编写的贝叶斯推断模型集成于组件化软件BayesCode中，该软件的源码托管于https://github.com/ThibaultLatrille/bayescode。
采用C++语言编写的模拟软件SimuEvol托管于https://github.com/ThibaultLatrille/SimuEvol。由于此类实证与模拟分析的运行耗时可达数周，因此本figshare数据仓库存储了贝叶斯推断模型（BayesCode）的输出结果，以及针对模拟数据集（由SimuEvol生成）与实证数据集的分析结果。
使用须知：
1. 克隆（或下载）托管于https://github.com/ThibaultLatrille/MutationSelectionDrift的MutationSelectionDrift仓库。
2. 将压缩包DataSimulatedExperiments.tar.xz解压至DataSimulated文件夹内。
3. 将压缩包DataEmpiricalExperiments.tar.xz解压至DataEmpirical文件夹内。
4. 将压缩包DataEmpiricalAnalysis.tar.xz解压至DataEmpirical文件夹的子文件夹Analysis中。