STELAR is a Dynamic Programming (DP) based software for estimating species trees given a set of rooted gene trees, such that triplet consistency (between a species tree and the gene trees) is maximized within a constrained search space. STELAR is fast, highly accurate and statistically consistent. The algorithm used is described in our paper "STELAR: A statistically consistent coalescent-based species trees estimation method by maximizing triplet consistency." (Paper link)
STELAR is freely available at https://github.com/islamazhar/STELAR. A step by step installation guide and other are also available there.
Species tree estimation is frequently based on phylogenomic approaches that use multiple genes from throughout the genome. However, estimating a species tree from a collection of gene trees can be complicated due to the presence of gene tree incongruence resulting from incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent process. Maximum likelihood and Bayesian MCMC methods can potentially result in accurate trees, but they do not scale well to large datasets.
We present STELAR (Species Tree Estimation by maximizing tripLet AgReement), a new fast and highly accurate statistically consistent coalescent-based method for estimating species trees from a collection of gene trees. We formalized the constrained triplet consensus (CTC) problem and showed that the solution to the CTC problem is a statistically consistent estimate of the species tree under the multi-species coalescent (MSC) model. STELAR is an efficient dynamic programming based solution to the CTC problem which is highly accurate and scalable. We evaluated the accuracy of STELAR in comparison with SuperTriplets, which is an alternate fast and highly accurate triplet-based supertree method, and with MP-EST and ASTRAL – two of the most popular and accurate coalescent-based methods. Experimental results suggest that STELAR matches the accuracy of ASTRAL and improves on MP-EST and SuperTriplets.
Theoretical and empirical results (on both simulated and real biological datasets) suggest that STELAR is a valuable technique for species tree estimation from gene tree distributions.
STELAR code uses code from the PhyloNet package by Luay Nakhleh (bioinfo.cs.rice.edu/phylonet). The Phylonet code base was previously used by DynaDup and ASTRAL (with permission from Authors), and STELAR is mostly based on DynaDup code base.
We are always looking for ways to improve our codes. For any bugs please email at: mazhar.buet11@gmail.com
If you use this code or STELAR tool in your research, please cite the following publication.
@article{islam2020stelar,
title={STELAR: A statistically consistent coalescent-based species tree estimation method by maximizing triplet consistency},
author={Islam, Mazharul and Sarker, Kowshika and Das, Trisha and Reaz, Rezwana and Bayzid, Md Shamsuzzoha},
journal={BMC Genomics},
volume={21},
number={1},
pages={1--13},
year={2020},
publisher={BioMed Central}
}