Chapter 1 About

With the widespread application of whole-genome sequencing (WGS) technologies, genomic data for pathogenic bacteria are rapidly expanding. Mutation detection based on reference genomes enables the rapid identification of adaptive mutations (e.g., drug resistance mutations, antigenic variations). While several studies have successfully identified genes under positive selection using public genomic datasets (Liu et al. (2022)), the lack of a unified framework for storing and analyzing bacterial mutation data hinders efficient data reuse.

Here we developed qMut, the R package designed for storage and rapid analysis of pathogenic bacterial mutations. This tutorial demonstrates its functionality using mutation data from more than 50000 Mycobacterium tuberculosis genomes.

References

Liu, Qinqin, Jian Zhu, Colin L Dulberger, Sierra Stanley, Sarah Wilson, Emily S Chung, Xiaojun Wang, et al. 2022. “Tuberculosis Treatment Failure Associated with Evolution of Antibiotic Resilience.” Science 378 (6624): 1111–18. https://doi.org/10.1126/science.abq2787.