evolBoosting Downloaded: 0 Viewed: 0 Developed By: Group of Evolutionary Genomics
The principle of this package is to use a machine learning method, boosting, to study the difference between selected population DNA samples and neutral samples. Then, boosting will produce a predictor via training (study) process. This predictor can then be used to predict new samples are whether selected or neutral.
Documentation & Usage:
evolBoosting is developed and maintained by CAS-MPG Partner Institute for Computational Biology(PICB) ,Chinese Academy of Sciences. The software is only free of charge for non-commercial users.
K. Lin, H. Li, C. Schloetterer and A. Futschik(2011) Distinguishing positive selection from neutral evolution: boosting the performance of summary statistics. Genetics 187: 229-244.
If you have any feedback or question concerning the tools you can further click the Project Website , or please feel free to contact us at lihaipengpicb.ac.cn.