Download
MiModD is a software package for genomic variant identification from next-generation sequencing (NGS) data with optimized usage of system resources and a user-friendly interface. For most model organism genomes it lets the user carry out a complete analysis from unaligned genomic NGS read data to an annotated list of variants on a regular Desktop PC within a few hours. Its user-interface is beginner-friendly and designed to encourage geneticists to analyze NGS data themselves without the help of a trained bioinformatician.
Features
- WGS analysis of model organism genomes even on single PCs and notebooks
- powerful tools for variant filtering and mapping
- integration into an existing Galaxy installation with a single command
- example datasets for testing
- online tutorial and extensive documentation
- platform-specific bundled distributions (many Linux flavours, OS X) to run and test in a pre-configured Galaxy instance without installation
Project Samples
Categories
Bio-InformaticsLicense
GNU General Public License version 3.0 (GPLv3)Follow MiModD
Other Useful Business Software
Get Avast Free Antivirus | Your top-rated shield against malware and online scams
Our antivirus software scans for security and performance issues and helps you to fix them instantly. It also protects you in real time by analyzing unknown files before they reach your desktop PC or laptop — all for free.
Rate This Project
Login To Rate This Project
User Reviews
-
MiModD is an easy-to-use software package being used by our lab to identify mutations in C. elegans. The author is very quick to respond to issues and helped us to get the program up and running for our needs.
-
A very simple and straightforward set of programs that allows the analysis and identification of mutations from whole genome sequence (WGS) data derived from genetically tractable model organisms. The programs come with a well written set of tutorials, that provide step-by-step instructions and assumes only a basic knowledge of the command line. The author was very helpful in helping us install and use this package when we first began using it in to analyse our data.