Mumame: A software tool for quantifying gene-specific point-mutations in shotgun metagenomic data
Journal article, 2019

Metagenomics has emerged as a central technique for studying the structure and function of microbial communities. Often the functional analysis is restricted to classification into broad functional categories. However, important phenotypic differences, such as resistance to antibiotics, are often the result of just one or a few point mutations in otherwise identical sequences. Bioinformatic methods for metagenomic analysis have generally been poor at accounting for this fact, resulting in a somewhat limited picture of important aspects of microbial communities. Here, we address this problem by providing a software tool called Mumame, which can distinguish between wildtype and mutated sequences in shotgun metagenomic data and quantify their relative abundances. We demonstrate the utility of the tool by quantifying antibiotic resistance mutations in several publicly available metagenomic data sets. We also identified that sequencing depth is a key factor to detect rare mutations. Therefore, much larger numbers of sequences may be required for reliable detection of mutations than for most other applications of shotgun metagenomics. Mumame is freely available online (

Mutation detection

Bioinformatic tools

Mutation frequencies


Statistical methods

Antibiotic resistance


Shruthi Magesh

University of Wisconsin Madison

SRM Institute of Science and Technology

Viktor Jonsson


Johan Bengtsson-Palme

University of Gothenburg

University of Wisconsin Madison

Metabarcoding and Metagenomics

25349708 (eISSN)

Vol. 3 e36236

Areas of Advance

Health Engineering

Subject Categories


Bioinformatics and Systems Biology

Computer Science



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