L. Nakhleh

The impact of model misspecification on phylogenetic network inference

This study evaluates how model misspecification affects phylogenetic network inference using simulated and biological data, finding that gene tree estimation error and substitution rate heterogeneity impact accuracy.

Comparing Inference under the MSC versus the MSC-with-Recombination

This study compares three methods for estimating population parameters under different coalescent models, showing that diCal2 performs worse despite being designed for recombination.

"Correcting'' gene trees to be more like species trees increases topological error when incomplete lineage sorting is high

This paper shows that gene tree correction methods can increase topological error when incomplete lineage sorting is high, suggesting that correction should consider the species phylogeny.

MaCroDNA: Accurate integration of single-cell DNA and RNA data for a deeper understanding of tumor heterogeneity

MaCroDNA integrates single-cell DNA and RNA data to better understand tumor heterogeneity, showing improved accuracy and speed over existing methods.

MoTERNN: Classifying the Mode of Cancer Evolution Using Recursive Neural Networks

This paper introduces MoTERNN, a recursive neural network that classifies cancer evolution modes from phylogenetic trees into four categories using simulated and real single-cell DNA sequencing data.

Phylogenetic Network Dissimilarity Measures That Take Branch Lengths Into Account

This paper introduces two phylogenetic network dissimilarity measures that consider both topology and branch lengths, and demonstrates their use in clustering inferred networks.

Phylovar: Towards scalable phylogeny-aware inference of single-nucleotide variations from single-cell DNA sequencing data

Phylovar improves scalability and accuracy of SNV detection in scDNAseq data by leveraging phylogenetic information, outperforming existing methods in speed and precision.

Supporting per-locus substitution rates improves the accuracy of species networks and avoids spurious reticulations

The paper improves species network accuracy by supporting per-locus substitution rates, reducing spurious reticulations in phylogenetic inference.

NestedBD: Bayesian Inference of Phylogenetic Trees From Single-Cell DNA Copy Number Profile Data Under a Birth-Death Model

This paper introduces NestedBD, a Bayesian method for inferring phylogenetic trees from single-cell DNA copy number data under a birth-death model, showing improved accuracy over existing methods.

Species Tree Inference on Data with Paralogs is Accurate Using Methods Intended to Deal with Incomplete Lineage Sorting

This study shows that species tree inference methods can accurately handle data with paralogs, even when incomplete lineage sorting is present.

Maximum Parsimony Inference of Phylogenetic Networks in the Presence of Polyploid Complexes

This paper introduces a method to infer phylogenetic networks from polyploid data, minimizing deep coalescences and distinguishing between auto- and allo-polyploidy.

Phylogenomic assessment of the role of hybridization and introgression in trait evolution

The paper presents a phylogenomic method to assess hybridization and introgression's role in trait evolution, showing gene flow can lead to misleading trait evolution hypotheses.

Variational Inference Using Approximate Likelihood Under the Coalescent With Recombination

This paper introduces a variational inference method for coalHMMs that learns evolutionary parameters and infers local genealogies with comparable accuracy to existing methods, using simulated data.

Practical Aspects of Phylogenetic Network Analysis Using PhyloNet

This paper demonstrates PhyloNet's functionalities for analyzing phylogenetic networks using simulated data and provides recommendations for data analysis and interpretation.

Empirical Performance of Tree-based Inference of Phylogenetic Networks

This study evaluates a tree-based method for inferring phylogenetic networks and finds it performs poorly compared to direct network space exploration.

Unifying Gene Duplication, Loss, and Coalescence on Phylogenetic Networks

This paper introduces a unified model for gene evolution incorporating ILS, GDL, and introgression, and develops an algorithm to estimate phylogenetic network parameters.

A Divide-and-Conquer Method for Scalable Phylogenetic Network Inference from Multi-locus Data

This paper introduces a scalable method for inferring phylogenetic networks from multi-locus data, achieving accurate results at a larger scale than existing methods.

Integrated Likelihood for Phylogenomics under a No-Common-Mechanism Model

This paper introduces a no-common-mechanism model for phylogenomics and derives an integrated likelihood for inferring species trees and networks from multiple gene trees.

Inference of Species Phylogenies from Bi-allelic Markers Using Pseudo-likelihood

This paper introduces a pseudo-likelihood method for inferring phylogenetic networks from bi-allelic markers, demonstrating scalability and robustness on simulated and biological data.

Inferring Phylogenetic Networks Using PhyloNet

The paper describes the evolution and features of PhyloNet, a software package for inferring phylogenetic networks from genetic data.

Bayesian Inference Of Phylogenetic Networks From Bi-allelic Genetic Markers

This paper introduces a Bayesian method for inferring phylogenetic networks from bi-allelic markers, demonstrating good accuracy and robustness on simulated and empirical data.

Co-estimating Reticulate Phylogenies and Gene Trees from Multi-locus Sequence Data

This paper introduces a Bayesian method to co-estimate species phylogenies and gene trees from multi-locus sequence data, accounting for reticulation and incomplete lineage sorting.