The rise of genomic big data has transformed many aspects of the decades-long research on phylogenetic relationship inference. To maximize information extracted from sequenced biomolecules, computational pipelines have been developed that include steps such as genome assembly, annotation and orthology identification, all of which are equipped with dedicated algorithms. Despite being remarkably powerful, these complex pipelines also set up high barriers in terms of data quality, bioinformatics expertise and computational capability. To ease the task of phylogenomic inference, Fritz Sedlazeck at Baylor College of Medicine, Christophe Dessimoz at the University of Lausanne and their colleagues cooperated to develop Read2Tree, an efficient and accurate method for building trees directly from raw sequencing reads.
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