Improved gene tree error correction in the presence of horizontal gene transfer

Bansal, Mukul S.; Wu, Yi-Chieh; Alm, Eric J.; Kellis, M

doi:10.1093/bioinformatics/btu806

Cited by 54 publications

(41 citation statements)

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“…Thus, the total transfer rate was twice the duplication rate, with an equal rate of additive and replacing transfers, and the loss rate was assigned to be equal to the sum of the duplication and additive transfer rates. These duplication, transfer, and loss rates are based on rates observed in real data and capture both datasets with lower rates of these events and datasets with a very high rate of these events [4]. For the low DTRL gene trees, the average gene tree leaf set size was 96.11, with an average of 2.37 additive transfers, 2.65 replacing transfers, and 2.19 duplication events per gene tree.…”

Section: Experimental Analysismentioning

confidence: 99%

On Inferring Additive and Replacing Horizontal Gene Transfers Through Phylogenetic Reconciliation

Kordi

Kundu

Bansal

2019

Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics

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Horizontal gene transfer is one of the most important mechanisms for microbial evolution and adaptation. It is well known that horizontal gene transfer can be either additive or replacing depending on whether the transferred gene adds itself as a new gene in the recipient genome or replaces an existing homologous gene. Yet, all existing phylogenetic techniques for the inference of horizontal gene transfer assume either that all transfers are additive or that all transfers are replacing. This limitation not only a ects the applicability and accuracy of these methods but also makes it di cult to distinguish between additive and replacing transfers. Here, we address this important problem by formalizing a phylogenetic reconciliation framework that simultaneously models both additive and replacing transfer events. Speci cally, we (1) introduce the DTRL reconciliation framework that explicitly models both additive and replacing transfer events, along with gene duplications and losses, (2) prove that the underlying computational problem is NP-hard, (3) perform the rst experimental study to assess the impact of replacing transfer events on the accuracy of the traditional DTL reconciliation model (which assumes that all transfers are additive) and demonstrate that traditional DTL reconciliation remains highly robust to the presence of replacing transfers, (4) propose a simple heuristic algorithm for DTRL reconciliation based on classifying transfer events inferred through DTL reconciliation as being replacing or additive, and (5) evaluate the classication accuracy of the heuristic under a range of evolutionary conditions. Thus, this work lays the methodological and algorithmic foundations for estimating DTRL reconciliations and distinguishing between additive and replacing transfers. An implementation of our heuristic for DTRL reconciliation is freely available open-source as part of the RANGER-DTL software package from https://compbio.engr.uconn.edu/software/ranger-dtl/.

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Section: Experimental Analysismentioning

confidence: 99%

On Inferring Additive and Replacing Horizontal Gene Transfers Through Phylogenetic Reconciliation

Kordi

Kundu

Bansal

2019

Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics

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Section: Experimental Analysismentioning

confidence: 99%

On Inferring Additive and Replacing Horizontal Gene Transfers Through Phylogenetic Reconciliation

Kordi

Kundu

Bansal

2020

Preprint

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Horizontal gene transfer is one of the most important mechanisms for microbial evolution and adaptation. It is well known that horizontal gene transfer can be either additive or replacing depending on whether the transferred gene adds itself as a new gene in the recipient genome or replaces an existing homologous gene. Yet, all existing phylogenetic techniques for the inference of horizontal gene transfer assume either that all transfers are additive or that all transfers are replacing. This limitation not only affects the applicability and accuracy of these methods but also makes it difficult to distinguish between additive and replacing transfers.Here, we address this important problem by formalizing a phylogenetic reconciliation framework that simultaneously models both additive and replacing transfer events. Specifically, we (1) introduce the DTRL reconciliation framework that explicitly models both additive and replacing transfer events, along with gene duplications and losses, (2) prove that the underlying computational problem is NP-hard, (3) perform the first experimental study to assess the impact of replacing transfer events on the accuracy of the traditional DTL reconciliation model (which assumes that all transfers are additive) and demonstrate that traditional DTL reconciliation remains highly robust to the presence of replacing transfers, (4) propose a simple heuristic algorithm for DTRL reconciliation based on classifying transfer events inferred through DTL reconciliation as being replacing or additive, and (5) evaluate the classification accuracy of the heuristic under a range of evolutionary conditions. Thus, this work lays the methodological and algorithmic foundations for estimating DTRL reconciliations and distinguishing between additive and replacing transfers.An implementation of our heuristic for DTRL reconciliation is freely available open-source as part of the RANGER-DTL software package from https://compbio.engr.uconn.edu/software/ranger-dtl/.

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“…The output is a transmission phylogeny T * . We perform a local search in a manner similar to TreeFix and TreeFix-DTL [25,26]. Using T ′ ← T ML as a starting point, we set C ′ to be the transmission cost of T ′ , and a candidate tree T is proposed by performing random NNI and SPR operations on T ′ .…”

Section: Algorithmic Detailsmentioning

confidence: 99%

“…Specifically, TreeFix-TP leverages both sequence and host information to reconstruct more accurate phylogenies than maximum likelihood on its own by minimizing the number of inter-host transmissions while maintaining statistical support. Similar error correction approaches have been successfully used for reconstruction of gene trees [25,26]; however, these previous methods are based on leveraging a known species phylogeny to error-correct and improve gene trees, and they are therefore inapplicable to the current setting where the goal is to reconstruct the strain tree itself (analogous to the species tree). We address this problem by leveraging intra-host strain diversity and defining a fitness function based on minimizing the number of inter-host transmissions implied by the underlying phylogeny.…”

Section: Introductionmentioning

confidence: 99%

TreeFix-TP: Phylogenetic Error-Correction for Infectious Disease Transmission Network Inference

Sledzieski

Zhang

Măndoiu

et al. 2019

Preprint

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Background: Many existing methods for estimation of infectious disease transmission networks use a phylogeny of the infecting strains as the basis for transmission network inference, and accurate network inference relies on accuracy of this underlying evolutionary history. However, phylogenetic reconstruction can be highly error prone and more sophisticated methods can fail to scale to larger outbreaks, negatively impacting downstream transmission network inference. Additionally, there are no currently available methods which are able to use within-host diversity to improve phylogenetic reconstruction. Results: We introduce a new method, TreeFix-TP, for accurate and scalable reconstruction of transmission phylogenies based on an error-correction framework. Our method uses intra-host strain diversity and host information to balance a parsimonious evaluation of the implied transmission network with statistical hypothesis testing on sequence data likelihood. The reconstructed tree minimizes the number of required disease transmissions while being as well supported by sequence data as the maximum likelihood phylogeny. We use a simulation framework for viral transmission and evolution to demonstrate that TreeFix-TP improves phylogenetic accuracy and downstream transmission network accuracy. We also use real data from ten HCV outbreaks and demonstrate how error-correction improves source detection. Conclusions:Our results show that using TreeFix-TP can lead to significant improvement in transmission phylogeny inference and that its performance is robust to variations in transmission and evolutionary parameters. Our experiments also demonstrate the importance of sampling multiple strain sequences from each infected host for accurate transmission network inference. TreeFix-TP is freely available open-source from https://compbio.engr.uconn.edu/software/treefix-tp/.

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Improved gene tree error correction in the presence of horizontal gene transfer

Cited by 54 publications

References 50 publications

On Inferring Additive and Replacing Horizontal Gene Transfers Through Phylogenetic Reconciliation

On Inferring Additive and Replacing Horizontal Gene Transfers Through Phylogenetic Reconciliation

On Inferring Additive and Replacing Horizontal Gene Transfers Through Phylogenetic Reconciliation

TreeFix-TP: Phylogenetic Error-Correction for Infectious Disease Transmission Network Inference

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