Novel Methodologies for Genome-scale Analysis of Multilocus Data

PI: Tandy Warnow

Funding: U.S. National Science Foundation grant DBI-1461364.

Project Overview: The Novel Methodologies for Genome-scale Analysis of Multilocus Data project is a joint effort among groups at Stanford University, UT Austin, Rice University, and Linfield College. The project aims to (1) devise new algorithms for species tree inference; (2) develop new methods for scalability of inference algorithms to large-scale genomic data; (3) perform mathematical, simulation-based, and empirical evaluations of the properties of species tree inference algorithms.

Highlights: The major effort for the Warnow Lab has been the development of computationally efficient methods for species tree estimation in the presence of gene tree discord due to incomplete lineage sorting. The highlights of this work include

Project Software: The Warnow Lab also produced other software, focusing on supertree estimation, multiple sequence alignment, metagenomic data analysis, and other topics. See this page for a nearly full list of software produced by the lab. Below, we provide links to software for estimating species trees from heterogeneous sets of gene trees, where heterogeneity is due to incomplete lineage sorting (ILS).

Summer Symposia and Software Schools: Among several symposia and software schools (some locally at the University of Illinois at Urbana-Champaign), the grant provides summer symposia and software schools to train researchers (from students through faculty) in new multiple sequence alignment methods, species tree estimation from sets of gene trees or their sequence alignments, and other topics within phylogenomics.

Publications: See my online publication list for all papers (many of which can be downloaded). Specific papers related to phylogenomic estimation (most of which are supported by this grant) are given below:

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.