MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences

MicroGMT: A Mutation Tracker for SARS-CoV-2 and Other Microbial Genome Sequences

Yue Xing, Xiao Li, Xiang Gao, Qunfeng Dong, Qunfeng Dong

With the continued spread of SARS-CoV-2 virus around the world, researchers often need to quickly identify novel mutations in newly sequenced SARS-CoV-2 genomes for studying the molecular evolution and epidemiology of the virus. We have developed a Python package, MicroGMT, which takes either raw sequence reads or assembled genome sequences as input and compares against database sequences to identify and characterize indels and point mutations. Although our default setting is optimized for SARS-CoV-2 virus, the package can be also applied to any other microbial genomes. The software is freely available at Github URL https://github.com/qunfengdong/MicroGMT.

2020

epidemiology, Bioinformatics, covid-19, SARS-CoV-2, molecular evolution, Mutation

10.3389/fmicb.2020.01502

Epidemiology and Health

Korean Society of Epidemiology

Microbiology