Phylogenetic and Phylogenomic Analyses for Large Datasets

Abstract

The phylogenetic tree is a main tool to study the evolutionary relationships among species. Computational methods for building phylogenetic trees from gene/protein sequences have been developed for decades and come of age. Efficient approaches, including distance-based methods, maximum likelihood methods, or classical maximum parsimony methods, are now able to analyze datasets with thousands of sequences. The advanced sequencing technologies have resulted in a huge amount of data including whole genomes. A number of methods have been proposed to analyze the wholegenome datasets, however, numerous challenges need to be addressed and solved to translate phylogenomic inferences into practices. In this paper, we will analyze widely-used methods to construct large phylogenetic trees, and available methods to build phylogenomic trees from whole-genome datasets. We will also give recommendations for best practices when performing phylogenetic and phylogenomic analyses. The paper will enable researchers to comprehend the state-ofthe-art methods and available software to efficiently study the evolutionary relationships among species from large datasets.