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MNHN-Tree-Tools: a toolbox for tree inference using multi-scale clustering of a set of sequences

2021; Oxford University Press; Volume: 37; Issue: 21 Linguagem: Inglês

10.1093/bioinformatics/btab430

1367-4811

Thomas Haschka, Loı̈c Ponger, Christophe Escudé, Julien Mozziconacci,

Environmental DNA in Biodiversity Studies

Abstract Summary Genomic sequences are widely used to infer the evolutionary history of a given group of individuals. Many methods have been developed for sequence clustering and tree building. In the early days of genome sequencing, these were often limited to hundreds of sequences but due to the surge of high throughput sequencing, it is now common to have millions of sampled sequences at hand. We introduce MNHN-Tree-Tools, a high performance set of algorithms that builds multi-scale, nested clusters of sequences found in a FASTA file. MNHN-Tree-Tools does not rely on multiple sequence alignment and can thus be used on large datasets to infer a sequence tree. Herein, we outline two applications: a human alpha-satellite repeats classification and a tree of life derivation from 16S/18S rDNA sequences. Availability and implementation Open source with a Zlib License via the Git protocol: https://gitlab.in2p3.fr/mnhn-tools/mnhn-tree-tools. Manual A detailed users guide and tutorial: https://gitlab.in2p3.fr/mnhn-tools/mnhn-tree-tools-manual/-/raw/master/manual.pdf. Website and FAQ http://treetools.haschka.net. Supplementary information Supplementary data are available at Bioinformatics online.