An alignment-free method for phylogeny estimation using maximum likelihood
Abstract Background While 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...
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BMC
2025-03-01
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| Series: | BMC Bioinformatics |
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| Online Access: | https://doi.org/10.1186/s12859-025-06080-w |
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| author | Tasfia Zahin Md. Hasin Abrar Mizanur Rahman Jewel Tahrina Tasnim Md. Shamsuzzoha Bayzid Atif Rahman |
| author_facet | Tasfia Zahin Md. Hasin Abrar Mizanur Rahman Jewel Tahrina Tasnim Md. Shamsuzzoha Bayzid Atif Rahman |
| author_sort | Tasfia Zahin |
| collection | DOAJ |
| description | Abstract Background While 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. Results Here, 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. Conclusions Results 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. |
| format | Article |
| id | doaj-art-138a6bd42e3d4f599051503ebc5f6571 |
| institution | DOAJ |
| issn | 1471-2105 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj-art-138a6bd42e3d4f599051503ebc5f65712025-08-20T03:05:44ZengBMCBMC Bioinformatics1471-21052025-03-0126111410.1186/s12859-025-06080-wAn alignment-free method for phylogeny estimation using maximum likelihoodTasfia Zahin0Md. Hasin Abrar1Mizanur Rahman Jewel2Tahrina Tasnim3Md. Shamsuzzoha Bayzid4Atif Rahman5Department of Computer Science and Engineering, Bangladesh University of Engineering and TechnologyDepartment of Computer Science and Engineering, Bangladesh University of Engineering and TechnologyDepartment of Computer Science and Engineering, Bangladesh University of Engineering and TechnologyDepartment of Computer Science and Engineering, Bangladesh University of Engineering and TechnologyDepartment of Computer Science and Engineering, Bangladesh University of Engineering and TechnologyDepartment of Computer Science and Engineering, Bangladesh University of Engineering and TechnologyAbstract Background While 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. Results Here, 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. Conclusions Results 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.https://doi.org/10.1186/s12859-025-06080-wPhylogeneticsAlignment-freek-merLikelihood |
| spellingShingle | Tasfia Zahin Md. Hasin Abrar Mizanur Rahman Jewel Tahrina Tasnim Md. Shamsuzzoha Bayzid Atif Rahman An alignment-free method for phylogeny estimation using maximum likelihood BMC Bioinformatics Phylogenetics Alignment-free k-mer Likelihood |
| title | An alignment-free method for phylogeny estimation using maximum likelihood |
| title_full | An alignment-free method for phylogeny estimation using maximum likelihood |
| title_fullStr | An alignment-free method for phylogeny estimation using maximum likelihood |
| title_full_unstemmed | An alignment-free method for phylogeny estimation using maximum likelihood |
| title_short | An alignment-free method for phylogeny estimation using maximum likelihood |
| title_sort | alignment free method for phylogeny estimation using maximum likelihood |
| topic | Phylogenetics Alignment-free k-mer Likelihood |
| url | https://doi.org/10.1186/s12859-025-06080-w |
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