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A k- mer-Based Approach for Phylogenetic Classification of Taxa in Environmental Genomic Data by Julia Van Etten; Timothy G Stephens; Debashish Bhattacharya is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Abstract In the age of genome sequencing, whole-genome data is readily and frequently generated, leading to a wealth of new information that can be used to advance various fields of research. New approaches, such as alignment-free phylogenetic methods that utilize k-mer-based distance scoring, are becoming increasingly popular given their ability to rapidly generate phylogenetic information from whole-genome data. However, these methods have not yet been tested using environmental data, which often tends to be highly fragmented and incomplete. Here, we compare the results of one alignment-free approach (which utilizes the D2 statistic) to traditional multi-gene maximum likelihood trees in 3 algal groups that have high-quality genome data available. In addition, we simulate lower-quality, fragmented genome data using these algae to test method robustness to genome quality and completeness. Finally, we apply the alignment-free approach to environmental metagenome assembled genome data of unclassified Saccharibacteria and Trebouxiophyte algae, and single-cell amplified data from uncultured marine stramenopiles to demonstrate its utility with real datasets. We find that in all insta

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Author

Julia Van Etten; Timothy G Stephens; Debashish Bhattacharya

Publisher

Oxford University Press (OUP)

Published

2023

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)