| Authors(s) | Shohei Kojima and Nicholas Parrish (RIKEN) with input from Atsushi Takeda and Michiaki Hamada (Waseda University) |
| Developer(s) | RIKEN Center for Integrative Medical Science |
| Written in | Python, C++ |
| Operating System | Unix |
| Platform | x86-64 |
| Stable Release | v1.0.1 (27 April 2022) |
| Initial Release | 27 March 2022 |
| License | MIT |
| Website | https://github.com/shohei-kojima/MEGAnE |
MEGAnE, Mobile Element Genotyping Analysis Environment, identifies and genotypes polymorphic mobile elements from short-read whole genome shotgun sequencing data (WGS). The current version does not support whole exome sequencing data nor is it tuned to detect somatic polymorphisms. The initial release of MEGAnE officially supports human and mouse datasets. However, we designed MEGAnE to allow analysis of other species, if the end user provides a repeat library (e.g. consensus sequences from RepBase or Dfam).
MEGAnE (眼鏡 in Japanese) is pronounced like "mega" + "ne" as in "net." In Japanese, megane refers to a glass/lens that fine-tunes our vision enabling us to see something more clearly or understand truth.
Features
MEGAnE was developed to enable statistical genetics (e.g. imputation, GWAS) using human mobile element variants. It incorporates several criteria that have not been considered in other similar tools to provide accurate individual genotype calls, and also enables cohort-wide joint calling. While use with low-depth or short-read WGS is possible, best results will be obtained when using 20x+ depth and 150bp+ paired end sequencing data.
See also
Homepage of the Genome Immunobiology RIKEN Hakubi Research team here.
References
| 1. Kojima, Shohei et al. (2022) “Mobile elements in human population-specific genome and phenotype divergence” |