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An alignment-free method for phylogeny estimation using maximum likelihood
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AI
DOI：10.1186/s12859-025-06080-w.png)
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Abstract
En 中文
BackgroundWhile alignment has traditionally been the primary approach for establishing homology prior to phylogenetic inference, alignment-free methods offer a simplified alternative, particularly beneficial when handling genome-wide data involving long sequences and complex events such as rearrangements. Moreover, alignment-free methods become crucial for data types like genome skims, where assembly is impractical. However, despite these benefits, alignment-free techniques have not gained widespread acceptance since they lack the accuracy of alignment-based techniques, primarily due to their reliance on simplified models of pairwise distance calculation.ResultsHere, we present a likelihood based alignment-free technique for phylogenetic tree construction. We encode the presence or absence of k-mers in genome sequences in a binary matrix, and estimate phylogenetic trees using a maximum likelihood approach. A likelihood based alignment-free method for phylogeny estimation is implemented for the first time in a software named Peafowl, which is available at: https://github.com/hasin-abrar/Peafowl-repo. We analyze the performance of our method on seven real datasets and compare the results with the state of the art alignment-free methods.ConclusionsResults suggest that our method is competitive with existing alignment-free tools. This indicates that maximum likelihood based alignment-free methods may in the future be refined to outperform alignment-free methods relying on distance calculation as has been the case in the alignment-based setting.
Keywords:
Phylogenetics
Alignment-free
k-mer
Likelihood