DOI: 10.5061/dryad.hdr7sqvsx
title: Data from: Improved robustness to gene tree incompleteness, estimation errors, and systematic homology errors with weighted TREE-QMC

description: Summary methods are widely used to reconstruct species trees from gene
 tres while accommodating discordance from incomplete lineage sorting;
 however, it is increasingly recognized that their accuracy can be
 negatively impacted by incomplete and/or error-ridden gene trees. To
 address the latter, Zhang and Mirarab (2022) updated the popular summary
 method ASTRAL so that it weights quartets based on gene tree branch
 lengths and support values. The implementation of these weighting schemes
 presented computational challenges, leading Zhang and Mirarab (2022) to
 replace ASTRAL's original algorithm (i.e., computing an exact
 solution within a constrained search space) in favor of search heuristics
 based on phylogenetic placement. Here, we show that these weighting
 schemes can be effectively leveraged within the Quartet Max Cut framework
 of Snir and Rao (2010), introducing weighted TREE-QMC. The incorporation
 of weighting schemes into TREE-QMC required only a small increase in time
 complexity compared to the unweighted algorithm; fortunately, the increase
 in runtime was also small, behaving more like a constant factor in our
 simulation study. Moreover, weighted TREE-QMC was fast and highly
 competitive with weighted ASTRAL, even outperforming it in terms of
 species tree accuracy on some challenging simulation conditions, such as
 large numbers of taxa. In reanalyzing two avian data sets, we found that
 weighting quartets by gene tree branch lengths can improve robustness to
 systematic homology errors and can be as effective as removing the
 impacted taxa from individual gene trees or removing the impacted gene
 trees entirely. Lastly, our study revealed that TREE-QMC was robust to
 extreme rates of missing taxa, suggesting its utility as a supertree
 method.
description: # Data from: Improved robustness to gene tree incompleteness, estimation
 errors, and systematic homology errors with weighted TREE-QMC 
 [https://doi.org/10.5061/dryad.hdr7sqvsx](https://doi.org/10.5061/dryad.hdr7sqvsx) ## Description of the data and file structure This repository contains data sets (gene trees and species trees) used in the weighted TREE-QMC evaluation study. For results on simulated data sets, we maintained the directory structure of the original studies (see the original studies for a complete description of model conditions and simulation parameters). ### Files and variables #### File: cloutier2019whole.tar.gz **Description:** Results on the avian data set from Cloutier et al. (2019); specifically, the best ML gene trees with abayes support *that we estimated* as well as the species trees *that we estimated*; see `README.txt` files in this directory for more information. #### File: mirarab2015astral2-extsim.species-trees.tar.gz **Description:** Results on the simulated data sets from Mirarab and Warnow (2015); specifically, the species trees *that we estimated* given the best ML gene trees either with sh support or abayes support. Species trees are in the directories labeled by `/` and have the naming convention `__gen.tre`. If `qsupp-wh` is tagged at the end of the file name, it means branch support was estimated using hybrid weighted quartets. #### File: mirarab2015astral2-extsim.estimated-gene-trees-abayes.tar.gz **Description:** Results on the simulated data sets from Mirarab and Warnow (2015); specifically, the gene trees with abayes support *that we estimated*. Gene trees are in directories labeled by `/`. #### File: morel2022asteroid-plants.tar.gz **Description:** Results on the plant data set from Morel et al (2022); specifically, the gene trees file *that we created* by combining individual best ML gene trees into a single file, the species trees *that we estimated* , and the new reference tree *that we created*; see `README.txt` file in this directory for more information. #### File: morel2022asteroid-ilssim.gene-trees.tar.gz **Description:** Results on simulated data sets from Morel al. (2022); specifically, the gene files *that we created* by combining individual gene trees into a single file. Gene trees are in the directories labeled by `_seed`. #### File: morel2022asteroid-ilssim.species-trees.tar.gz **Description:** Results on simulated data sets from Morel et al. (2023); specifically, the species trees *that we estimated* from the (combined) best ML gene trees. Species trees are in the directories labeled by `_seed` and have the naming convention `.tre`. If `qsupp-wn` is tagged at the end of the file name, it means branch support was estimated using (unweighted) weighted quartets. #### File: zhang2022weighting-gteesim.species-trees.tar.gz **Description:** Results on simulated data sets from Zhang and Mirarab (2022); specifically, the species trees *that we estimated* from best ML gene trees with abayes and bootstrap support. Species trees are in the directories labeled by and have the naming convention `__bps_gen.tre`. If `qsupp-wh` is tagged at the end of the file name, it means branch support was estimated using hybrid weighted quartets. #### File: wu2024genomes.tar.gz **Description:** Results on the avian data set from Wu et al. (2024); specifically, the best ML gene trees with abayes support *that we estimated* as well as species trees *that we estimated*; see `README.txt` files in this directory for more information. #### Code/software Source code for weighted TREE-QMC is available on Github: https://github.com/molloy-lab/TREE-QMC ## Access information Data was derived from the following sources: * **Cloutier et al (2019)** * Paper: [https://doi.org/10.1093/sysbio/syz019](https://doi.org/10.1093/sysbio/syz019) * Data: [http://dx.doi.org/10.5061/dryad.fj02s0j](http://doi.org/10.5061/dryad.fj02s0j). * **Mirarab and Warnow (2015)** * Paper: [https://doi.org/10.1093/bioinformatics/btv234](https://doi.org/10.1093/bioinformatics/btv234) * Data: [https://doi.org/doi:10.6076/D10C7C](https://doi.org/doi:10.6076/D10C7C) * **Morel et al. (2023)** * Paper: [https://doi.org/10.1093/bioinformatics/btac832](https://doi.org/10.1093/bioinformatics/btac832) * Data: [https://cme.h-its.org/exelixis/material/asteroid_data.tar.gz](https://cme.h-its.org/exelixis/material/asteroid_data.tar.gz) * **Wu et al. (2024)** * Paper: [https://doi.org/10.1073/pnas.2319696121](https://doi.org/10.1073/pnas.2319696121) * **Zhang and Mirarab (2022)** * Paper: [https://doi.org/10.1093/molbev/msac215](https://doi.org/10.1093/molbev/msac215) * Data: [https://github.com/chaoszhang/Weighted-ASTRAL_data](https://github.com/chaoszhang/Weighted-ASTRAL_data), [https://doi.org/10.6076/D1WK5R](https://doi.org/10.6076/D1WK5R)