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Although many tools are available to study variation and its impact in single genomes, there is a lack of algorithms for finding such variation in metagenomes. This hampers the interpretation of metagenomics sequencing datasets, which are increasingly acquired in research on the (human) microbiome, in environmental studies and in the study of processes in the production of foods and beverages.
(Nijkamp et al., 2013) Exploring variation-aware contig graphs for (comparative) metagenomics using MaryGold. Bioinformatics.