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

Journal article
Authors Shruthi Magesh
Viktor Jonsson
Johan Bengtsson-Palme
Published in Metabarcoding and Metagenomics
Volume 3
Pages 59–67
ISSN 2534-9708
Publication year 2019
Published at Centre for antibiotic resistance research, CARe
Institute of Biomedicine, Department of Infectious Medicine
Pages 59–67
Language en
Keywords Antibiotic resistance, bioinformatic tools, metagenomics, mutation frequencies, mutation detection, statistical methods
Subject categories Bioinformatics and Systems Biology


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 (

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