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Documents authored by Christensen, Sarah

Document
DOI: 10.4230/LIPIcs.WABI.2020.15
Advancing Divide-And-Conquer Phylogeny Estimation Using Robinson-Foulds Supertrees

Authors: Xilin Yu, Thien Le, Sarah Christensen, Erin K. Molloy, and Tandy Warnow

Published in: LIPIcs, Volume 172, 20th International Workshop on Algorithms in Bioinformatics (WABI 2020)

Abstract
One of the Grand Challenges in Science is the construction of the Tree of Life, an evolutionary tree containing several million species, spanning all life on earth. However, the construction of the Tree of Life is enormously computationally challenging, as all the current most accurate methods are either heuristics for NP-hard optimization problems or Bayesian MCMC methods that sample from tree space. One of the most promising approaches for improving scalability and accuracy for phylogeny estimation uses divide-and-conquer: a set of species is divided into overlapping subsets, trees are constructed on the subsets, and then merged together using a "supertree method". Here, we present Exact-RFS-2, the first polynomial-time algorithm to find an optimal supertree of two trees, using the Robinson-Foulds Supertree (RFS) criterion (a major approach in supertree estimation that is related to maximum likelihood supertrees), and we prove that finding the RFS of three input trees is NP-hard. We also present GreedyRFS (a greedy heuristic that operates by repeatedly using Exact-RFS-2 on pairs of trees, until all the trees are merged into a single supertree). We evaluate Exact-RFS-2 and GreedyRFS, and show that they have better accuracy than the current leading heuristic for RFS.
Cite as

Xilin Yu, Thien Le, Sarah Christensen, Erin K. Molloy, and Tandy Warnow. Advancing Divide-And-Conquer Phylogeny Estimation Using Robinson-Foulds Supertrees. In 20th International Workshop on Algorithms in Bioinformatics (WABI 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 172, pp. 15:1-15:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{yu_et_al:LIPIcs.WABI.2020.15,
  author =	{Yu, Xilin and Le, Thien and Christensen, Sarah and Molloy, Erin K. and Warnow, Tandy},
  title =	{{Advancing Divide-And-Conquer Phylogeny Estimation Using Robinson-Foulds Supertrees}},
  booktitle =	{20th International Workshop on Algorithms in Bioinformatics (WABI 2020)},
  pages =	{15:1--15:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-161-0},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{172},
  editor =	{Kingsford, Carl and Pisanti, Nadia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2020.15},
  URN =		{urn:nbn:de:0030-drops-128048},
  doi =		{10.4230/LIPIcs.WABI.2020.15},
  annote =	{Keywords: supertrees, divide-and-conquer, phylogeny estimation}
}
Document
DOI: 10.4230/LIPIcs.WABI.2019.4
TRACTION: Fast Non-Parametric Improvement of Estimated Gene Trees

Authors: Sarah Christensen, Erin K. Molloy, Pranjal Vachaspati, and Tandy Warnow

Published in: LIPIcs, Volume 143, 19th International Workshop on Algorithms in Bioinformatics (WABI 2019)

Abstract
Gene tree correction aims to improve the accuracy of a gene tree by using computational techniques along with a reference tree (and in some cases available sequence data). It is an active area of research when dealing with gene tree heterogeneity due to duplication and loss (GDL). Here, we study the problem of gene tree correction where gene tree heterogeneity is instead due to incomplete lineage sorting (ILS, a common problem in eukaryotic phylogenetics) and horizontal gene transfer (HGT, a common problem in bacterial phylogenetics). We introduce TRACTION, a simple polynomial time method that provably finds an optimal solution to the RF-Optimal Tree Refinement and Completion Problem, which seeks a refinement and completion of an input tree t with respect to a given binary tree T so as to minimize the Robinson-Foulds (RF) distance. We present the results of an extensive simulation study evaluating TRACTION within gene tree correction pipelines on 68,000 estimated gene trees, using estimated species trees as reference trees. We explore accuracy under conditions with varying levels of gene tree heterogeneity due to ILS and HGT. We show that TRACTION matches or improves the accuracy of well-established methods from the GDL literature under conditions with HGT and ILS, and ties for best under the ILS-only conditions. Furthermore, TRACTION ties for fastest on these datasets. TRACTION is available at https://github.com/pranjalv123/TRACTION-RF and the study datasets are available at https://doi.org/10.13012/B2IDB-1747658_V1.
Cite as

Sarah Christensen, Erin K. Molloy, Pranjal Vachaspati, and Tandy Warnow. TRACTION: Fast Non-Parametric Improvement of Estimated Gene Trees. In 19th International Workshop on Algorithms in Bioinformatics (WABI 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 143, pp. 4:1-4:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{christensen_et_al:LIPIcs.WABI.2019.4,
  author =	{Christensen, Sarah and Molloy, Erin K. and Vachaspati, Pranjal and Warnow, Tandy},
  title =	{{TRACTION: Fast Non-Parametric Improvement of Estimated Gene Trees}},
  booktitle =	{19th International Workshop on Algorithms in Bioinformatics (WABI 2019)},
  pages =	{4:1--4:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-123-8},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{143},
  editor =	{Huber, Katharina T. and Gusfield, Dan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2019.4},
  URN =		{urn:nbn:de:0030-drops-110347},
  doi =		{10.4230/LIPIcs.WABI.2019.4},
  annote =	{Keywords: Gene tree correction, horizontal gene transfer, incomplete lineage sorting}
}
Document
DOI: 10.4230/LIPIcs.WABI.2017.27
Optimal Completion of Incomplete Gene Trees in Polynomial Time Using OCTAL

Authors: Sarah Christensen, Erin K. Molloy, Pranjal Vachaspati, and Tandy Warnow

Published in: LIPIcs, Volume 88, 17th International Workshop on Algorithms in Bioinformatics (WABI 2017)

Abstract
Here we introduce the Optimal Tree Completion Problem, a general optimization problem that involves completing an unrooted binary tree (i.e., adding missing leaves) so as to minimize its distance from a reference tree on a superset of the leaves. More formally, given a pair of unrooted binary trees (T,t) where T has leaf set S and t has leaf set R, a subset of S, we wish to add all the leaves from S \ R to t so as to produce a new tree t' on leaf set S that has the minimum distance to T. We show that when the distance is defined by the Robinson-Foulds (RF) distance, an optimal solution can be found in polynomial time. We also present OCTAL, an algorithm that solves this RF Optimal Tree Completion Problem exactly in quadratic time. We report on a simulation study where we complete estimated gene trees using a reference tree that is based on a species tree estimated from a multi-locus dataset. OCTAL produces completed gene trees that are closer to the true gene trees than an existing heuristic approach, but the accuracy of the completed gene trees computed by OCTAL depends on how topologically similar the estimated species tree is to the true gene tree. Hence, under conditions with relatively low gene tree heterogeneity, OCTAL can be used to provide highly accurate completions of estimated gene trees. We close with a discussion of future research.
Cite as

Sarah Christensen, Erin K. Molloy, Pranjal Vachaspati, and Tandy Warnow. Optimal Completion of Incomplete Gene Trees in Polynomial Time Using OCTAL. In 17th International Workshop on Algorithms in Bioinformatics (WABI 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 88, pp. 27:1-27:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{christensen_et_al:LIPIcs.WABI.2017.27,
  author =	{Christensen, Sarah and Molloy, Erin K. and Vachaspati, Pranjal and Warnow, Tandy},
  title =	{{Optimal Completion of Incomplete Gene Trees in Polynomial Time Using OCTAL}},
  booktitle =	{17th International Workshop on Algorithms in Bioinformatics (WABI 2017)},
  pages =	{27:1--27:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-050-7},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{88},
  editor =	{Schwartz, Russell and Reinert, Knut},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2017.27},
  URN =		{urn:nbn:de:0030-drops-76392},
  doi =		{10.4230/LIPIcs.WABI.2017.27},
  annote =	{Keywords: phylogenomics, missing data, coalescent-based species tree estimation, gene trees}
}
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