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Computing Phylo-<inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="romashchenko-ieq1-3278049.gif"/></alternatives></inline-formula>-Mers
- Source :
- IEEE/ACM Transactions on Computational Biology and Bioinformatics; September 2023, Vol. 20 Issue: 5 p2889-2897, 9p
- Publication Year :
- 2023
-
Abstract
- Finding the correct position of new sequences within an established phylogenetic tree is an increasingly relevant problem in evolutionary bioinformatics and metagenomics. Recently, alignment-free approaches for this task have been proposed. One such approach is based on the concept of phylogenetically-informative <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="romashchenko-ieq3-3278049.gif"/></alternatives></inline-formula>-mers or phylo-<inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="romashchenko-ieq4-3278049.gif"/></alternatives></inline-formula>-mers for short. In practice, phylo-<inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="romashchenko-ieq5-3278049.gif"/></alternatives></inline-formula>-mers are inferred from a set of related reference sequences and are equipped with scores expressing the probability of their appearance in different locations within the input reference phylogeny. Computing phylo-<inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="romashchenko-ieq6-3278049.gif"/></alternatives></inline-formula>-mers, however, represents a computational bottleneck to their applicability in real-world problems such as the phylogenetic analysis of metabarcoding reads and the detection of novel recombinant viruses. Here we consider the problem of phylo-<inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="romashchenko-ieq7-3278049.gif"/></alternatives></inline-formula>-mer computation: how can we efficiently find all <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="romashchenko-ieq8-3278049.gif"/></alternatives></inline-formula>-mers whose probability lies above a given threshold for a given tree node? We describe and analyze algorithms for this problem, relying on branch-and-bound and divide-and-conquer techniques. We exploit the redundancy of adjacent windows of the alignment to save on computation. Besides computational complexity analyses, we provide an empirical evaluation of the relative performance of their implementations on simulated and real-world data. The divide-and-conquer algorithms are found to surpass the branch-and-bound approach, especially when many phylo-<inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="romashchenko-ieq9-3278049.gif"/></alternatives></inline-formula>-mers are found.
Details
- Language :
- English
- ISSN :
- 15455963 and 15579964
- Volume :
- 20
- Issue :
- 5
- Database :
- Supplemental Index
- Journal :
- IEEE/ACM Transactions on Computational Biology and Bioinformatics
- Publication Type :
- Periodical
- Accession number :
- ejs64209361
- Full Text :
- https://doi.org/10.1109/TCBB.2023.3278049