phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things)

Revell, Liam J.

doi:10.7717/peerj.16505

Cited by 32 publications

(16 citation statements)

References 149 publications

(245 reference statements)

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“…A tanglegram (Fig. 3) (Revell 2024) corroborates that our tree and the maximum likelihood tree deliver similar answers.…”

Section: Resultssupporting

confidence: 79%

Estimating Genome-wide Phylogenies Using Probabilistic Topic Modeling

Khodaei,

Edwards,

Beerli

2023

Preprint

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Inferring the evolutionary history of species or populations employing multilocus analysis is gaining ground in phylogenetic analysis. We developed an alignment-free method to infer the multilocus species tree, which is implemented in the Python package TopicContml. The method operates in two primary stages. First, it uses probabilistic topic modeling (specifically, Latent Dirichlet Allocation or LDA) to extract topic frequencies from k-mers, which are in turn derived from multilocus DNA sequences. Second, these extracted frequencies serve as an input for the program Contmlin the PHYLIP package, which is used to generate a species tree. We evaluated the performance of our method with biological and simulated datasets: a dataset with 14 DNA sequence loci from 78-92 individuals from two Australian bird species distributed in 9 populations, and a second dataset of 67317 autosomal loci and 4157 X-chromosome loci of 6 species in theAnopheles gambiaecomplex, and several simulated data sets. Our empirical results and simulated data suggest that our method is efficient and statistically accurate. We also assessed the uncertainty of the estimated relationships among clades using a bootstrap procedure for aligned data and fork-mers.

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“…A tanglegram (Fig. 3) (Revell 2024) corroborates that our tree and the maximum likelihood tree deliver similar answers.…”

Section: Resultssupporting

confidence: 79%

Estimating Genome-wide Phylogenies Using Probabilistic Topic Modeling

Khodaei,

Edwards,

Beerli

2023

Preprint

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“…Subsequently, five genomes were removed due to excessive branch lengths. The ML tree was visualized with R v4.3.1 and the following packages: ape v5.7.1 (Paradis et al, 2004), phytools v 1.9-16 (Revell, 2024), and ggtree v 3.8.2 (Yu et al, 2017).…”

Section: Methodsmentioning

confidence: 99%

Bacterial strain nomenclature in the genomic era: Life Identification Numbers using a gene-by-gene approach

Palma,

Hennart,

Jolley

et al. 2024

Preprint

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Unified strain taxonomies are crucial for fostering international communication in microbiological research and for the epidemiological surveillance of bacterial pathogens. While multilocus sequence typing (MLST) has served as a foundation of strain taxonomy for two decades, whole genome sequencing enables more precise classifications and significantly improves discriminatory resolution. The core genome-wide extension of MLST (known as cgMLST) thus holds great promise for strain genotyping and classification, but its implementation faces challenges that include missing data, potential instability of cluster-based nomenclatures, and the necessity to ensure backwards compatibility with MLST identifiers. Life Identification Number (LIN) codes offer a solution by providing multi-level classification groups that are inherently stable. Here, we present, consolidate, and extend the cgMLST-based LIN code approach. We first develop a nicknaming system for LIN code prefixes, which enables flexible human-readable strain nomenclatures. UsingKlebsiella pneumoniae(Kp) as an example, LIN code nicknames were attributed by inheritance from MLST identifiers, thus perpetuating the legacy of MLST nomenclatures in the genomic era. We show that while 7-gene MLST sometimes conflates unrelated sublineages into the same ST, cgMLST-based LIN codes are highly concordant with phylogenetic relationships. We implement this novel LIN code-based nomenclature in the BIGSdb platform, and illustrate, with Pathogenwatch, how it can also be used in other genomic epidemiology platforms. Finally, we demonstrate the value of LIN codes for tracking the strain diversity within high-risk internationally disseminated clonal groups of Kp and protracted outbreaks. Given its stability, precision, and flexibility, we recommend the adoption of the cgMLST-based LIN code taxonomic approach for Kp and suggest that this approach is widely applicable to other bacterial pathogens.

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“…The viruses in the phylogenetic tree for which the host cannot be recognized through published literature or information provided by the authors are disregarded. The co-phylogenetic plots (or ‘tanglegram’) generated using the R package phytools [ 40 ] visually represent the correspondence between host and virus trees, with lines connecting hosts and their respective viruses. The event-based program eMPRess [ 41 ] was employed to determine whether the pairs of virus groups and their hosts undergo coevolution.…”

Section: Methodsmentioning

confidence: 99%

Discovery of novel RNA viruses through analysis of fungi-associated next-generation sequencing data

Lu,

Dai,

Xue

et al. 2024

BMC Genomics

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Background Like all other species, fungi are susceptible to infection by viruses. The diversity of fungal viruses has been rapidly expanding in recent years due to the availability of advanced sequencing technologies. However, compared to other virome studies, the research on fungi-associated viruses remains limited. Results In this study, we downloaded and analyzed over 200 public datasets from approximately 40 different Bioprojects to explore potential fungal-associated viral dark matter. A total of 12 novel viral sequences were identified, all of which are RNA viruses, with lengths ranging from 1,769 to 9,516 nucleotides. The amino acid sequence identity of all these viruses with any known virus is below 70%. Through phylogenetic analysis, these RNA viruses were classified into different orders or families, such as Mitoviridae, Benyviridae, Botourmiaviridae, Deltaflexiviridae, Mymonaviridae, Bunyavirales, and Partitiviridae. It is possible that these sequences represent new taxa at the level of family, genus, or species. Furthermore, a co-evolution analysis indicated that the evolutionary history of these viruses within their groups is largely driven by cross-species transmission events. Conclusions These findings are of significant importance for understanding the diversity, evolution, and relationships between genome structure and function of fungal viruses. However, further investigation is needed to study their interactions.

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phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things)

Cited by 32 publications

References 149 publications

Estimating Genome-wide Phylogenies Using Probabilistic Topic Modeling

Estimating Genome-wide Phylogenies Using Probabilistic Topic Modeling

Bacterial strain nomenclature in the genomic era: Life Identification Numbers using a gene-by-gene approach

Discovery of novel RNA viruses through analysis of fungi-associated next-generation sequencing data

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