RootDigger: a root placement program for phylogenetic trees

Bettisworth, Ben; Stamatakis, Alexandros

doi:10.1101/2020.02.13.935304

Cited by 8 publications

(18 citation statements)

References 14 publications

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“…Our results suggest that non-reversible amino-acid models are more useful for inferring root positions than non-reversible DNA models, which is consistent with results from previous simulations using the NR-DNA model (Bettisworth and Stamatakis 2020). One explanation for this difference between the NR-DNA and the NR-AA models is the bigger character-state space of the NR-AA models.…”

Section: Discussionsupporting

confidence: 90%

“…In addition, since non-reversible models naturally incorporate a notion of time, the position of the root on the tree is a parameter that is estimated as part of the ML tree inference. Since the incorporation of non-reversible models in efficient ML tree inference software is relatively new , we still understand relatively little about the ability of non-reversible models to infer the root of a phylogenetic tree, although a recent simulation study has shown some encouraging results (Bettisworth and Stamatakis 2020).…”

Section: Main Textmentioning

confidence: 99%

“…There is strong empirical evidence that molecular evolutionary processes are rarely reversible (Squartini and Arndt 2008;Naser-Khdour, et al 2019), but few studies have explored the accuracy of non-reversible substitution models to root phylogenetic trees (Huelsenbeck, et al 2002;Yap and Speed 2005;Williams, et al 2015;Cherlin, et al 2018;Bettisworth and Stamatakis 2020). Most studies that have looked at this question in the past have focused on either simulated datasets (Huelsenbeck, et al 2002;Jayaswal, et al 2011;Cherlin, et al 2018;Bettisworth and Stamatakis 2020) or relatively small empirical datasets (Yang and Roberts 1995;Yap and Speed 2005;Jayaswal, et al 2011;Heaps, et al 2014;Williams, et al 2015;Cherlin, et al 2018). In both cases, the addressed substitution models were nucleotide models, and to our knowledge, no study has yet investigated the potential of amino acid substitution models in inferring the root placement of phylogenetic trees.…”

Section: Main Textmentioning

confidence: 99%

“…A recent study investigated the ability of non-reversible nucleotide models to infer the root placement of phylogenetic trees (Bettisworth and Stamatakis 2020). This study showed that IQ-TREE performs competitively with a new rooting tool, RootDigger.…”

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confidence: 99%

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Assessing Confidence in Root Placement on Phylogenies: An Empirical Study Using Non-Reversible Models for Mammals

Naser-Khdour

Minh

Lanfear

2020

Preprint

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Using time-reversible Markov models is a very common practice in phylogenetic analysis, because although we expect many of their assumptions to be violated by empirical data, they provide high computational efficiency. However, these models lack the ability to infer the root placement of the estimated phylogeny. In order to compensate for the inability of these models to root the tree, many researchers use external information such as using outgroup taxa or additional assumptions such as molecular-clocks. In this study, we investigate the utility of non-reversible models to root empirical phylogenies and introduce a new bootstrap measure, the rootstrap, which provides information on the statistical support for any given root position.Availability and implementationA python script for calculating rootstrap support values is available at https://github.com/suhanaser/Rootstrap.

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Section: Discussionsupporting

confidence: 90%

Section: Main Textmentioning

confidence: 99%

Section: Main Textmentioning

confidence: 99%

mentioning

confidence: 99%

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Assessing Confidence in Root Placement on Phylogenies: An Empirical Study Using Non-Reversible Models for Mammals

Naser-Khdour

Minh

Lanfear

2020

Preprint

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“…Rooting with RootDigger. To further assess the uncertainty of the root location via a mathematically distinct approach, we also performed analyses with our RootDigger tool (40).…”

Section: Data Preparation and Analysis Pipelinementioning

confidence: 99%

Phylogenetic analysis of SARS-CoV-2 data is difficult

Morel

Barbera

Czech

et al. 2020

Preprint

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Numerous studies covering some aspects of SARS-CoV-2 data analyses are being published on a daily basis, including a regularly updated phylogeny on nextstrain.org. Here, we review the difficulties of inferring reliable phylogenies by example of a data snapshot comprising all virus sequences available on May 5, 2020 from gisaid.org. We find that it is difficult to infer a reliable phylogeny on these data due to the large number of sequences in conjunction with the low number of mutations. We further find that rooting the inferred phylogeny with some degree of confidence either via the bat and pangolin outgroups or by applying novel computational methods on the ingroup phylogeny does not appear to be possible. Finally, an automatic classification of the current sequences into sub-classes based on statistical criteria is also not possible, as the sequences are too closely related. We conclude that, although the application of phylogenetic methods to disentangle the evolution and spread of COVID-19 provides some insight, results of phylogenetic analyses, in particular those conducted under the default settings of current phylogenetic inference tools, as well as downstream analyses on the inferred phylogenies, should be considered and interpreted with extreme caution.

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Parameter Estimation and Species Tree Rooting Using ALE and GeneRax

Williams

Davín

Morel

et al. 2023

Genome Biology and Evolution

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ALE and GeneRax are tools for probabilistic gene tree-species tree reconciliation. Based on a common underlying statistical model of how gene trees evolve along species trees, these methods rely on gene versus species tree discordance to infer gene duplication, transfer and loss events, map gene family origins and root species trees. Published analyses have used these methods to root species trees of Archaea, Bacteria and several eukaryotic groups, as well as to infer ancestral gene repertoires. However, it was recently suggested that reconciliation-based estimates of duplication and transfer events using the ALE/GeneRax model were unreliable, with potential implications for species tree rooting. Here, we assess these criticisms and find that the methods are accurate when applied to simulated data and in generally good agreement with alternative methodological approaches on empirical data. In particular, ALE recovers variation in gene duplication and transfer frequencies across lineages that is consistent with the known biology of studied clades. In plants and opisthokonts, ALE recovers the consensus species tree root; in Bacteria - where there is less certainty about the root position - ALE agrees with alternative approaches on the most likely root region. Overall, ALE and related approaches are promising tools for studying genome evolution.

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RootDigger: a root placement program for phylogenetic trees

Cited by 8 publications

References 14 publications

Assessing Confidence in Root Placement on Phylogenies: An Empirical Study Using Non-Reversible Models for Mammals

Assessing Confidence in Root Placement on Phylogenies: An Empirical Study Using Non-Reversible Models for Mammals

Phylogenetic analysis of SARS-CoV-2 data is difficult

Parameter Estimation and Species Tree Rooting Using ALE and GeneRax

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