Skip to main content

Treehouse: a user-friendly application to obtain subtrees from large phylogenies



Phylogenetic trees that contain hundreds to thousands of taxa are now routinely generated. Retrieving the relationships among a subset of taxa in these large phylogenies can be a challenging or time-consuming task. Addressing this challenge requires the development of tools that facilitate the easy retrieval of subtrees from any user-specified set of taxa in a given phylogeny.


We developed treehouse, an open source tool that enables the retrieval of any subtree from a given large phylogeny. With a three-step workflow, treehouse successfully allows a user to obtain a subtree from any phylogeny. Treehouse can help researchers to explore the relationships among any set of taxa from across the tree of life. Treehouse is implemented as a shiny application in the R programming language. Treehouse software and usage instructions are publicly available at


Evolutionary biology relies on understanding the phylogenetic relationships among sets of genes, traits, and organisms under investigation. However, large phylogenies that contain hundreds of taxa are increasingly becoming inaccessible to researchers interested in the relationships of just a few representatives. For example, some phylogenies are so large that taxon information is often challenging or impossible to visualize and is often excluded [1,2,3,4]; similarly, the lengths of many internal branches are often very short and the constraints of displaying a large tree in a letter-sized page make the tracing of relationships among a subset of taxa challenging and unnecessarily time-consuming. These issues will increase in frequency as the numbers of taxa included in phylogenies of genes, metagenomes, genomes, etc. continues to rapidly rise.

To address these issues, we introduce treehouse, a user-friendly application with minimal dependencies that facilitates the retrieval of subtrees from any user-specified set of taxa in a given phylogeny. Our simple three-step workflow allows users to obtain subtrees from a curated and growing database of large-scale phylogenetic trees from across the tree of life. Additionally, users may obtain subtrees from their own phylogenies which, can facilitate data exploration and inter-disciplinary collaboration. For easy integration into pre-existing project workflows, subtrees obtained from treehouse can be easily be downloaded as a newick file or PDF file that retains branch length information. Treehouse enables beginner and expert evolutionary biologists alike to reap the benefits of large-scale phylogenetic projects and use them to test evolutionary-based hypotheses.

Main text

Materials and methods

Data acquisition

The treehouse contains a database of 20 representative large phylogenies from across the tree of life (Table 1).

Table 1 Curated phylogenies currently available in treehouse’s database

Description of the software

Using treehouse requires the R packages phytools, version 0.6–60 [21], and shiny, version 1.2.0 ( Dependencies of phytools includes maps, version 3.3.0 (, and ape, version 5.3 [22]. To present the phylogeny as depicted by the original authors, phylogenies from treehouse’s database are rooted. The taxa chosen to root the phylogeny on are inferred from figures presented in the original manuscript or, in the case of phylogenies presented without taxa names, personal communications with the authors. Phylogenies are rooted using phytoolss root() function. Using the list of taxa provided by the user, treehouse determines the list of taxa to remove from the phylogeny using the setdiff() function. The resulting list is then used to remove taxa in the phylogeny using phytoolss drop.tip() function. To write out the resulting phylogeny in a newick-formatted text file or display it in a scalable-vector-graphic-formatted pdf file, we use the write.tree() and plot.phylo() functions in Ape, respectively. To create a user-friendly and intuitive user-interface, we used shiny.


A three-step workflow to obtain subtrees

Treehouse is designed to have a simple user-interface that guides a user through an intuitive three-step workflow (Fig. 1A) and user interface (Fig. 1B).

Fig. 1

A simple three-step workflow for using treehouse. A Using treehouse requires three simple steps: (1) Tree selection: select a phylogeny from the treehouse database or a user-provided phylogeny that you want a subtree for; (2) Taxon selection: upload a list of taxa that a user wants to include in the subtree; and (3) Subtree output: download the newick-formatted text file or scalable-vector-graphic-formatted pdf file of the subtree. B Treehouse’s user interface features a navigation bar (a) to toggle between phylogenies available in treehouse’s databases for animals, fungi, plants, and the tree of life (left) and a user provided phylogeny in userTree (right). b To enable easy usage of treehouse, quick start directions are displayed. i A dropdown menu allows for selection of a larger phylogeny to obtain a subtree from when using phylogenies in treehouse’s database. When using userTree, a browser function allows a user to upload their own phylogeny. ii A browser function allows the user to upload a list of taxa for the desired subtree. c A list of all possible taxa in phylogeny is provided

  1. 1.

    Tree selection

    A user can choose between five tabs—userTree, Animals, Fungi, Plants, and Tree of Life—located at the top of the user interface (Fig. 1Ba). When using phylogenies from the treehouse database, a user selects the desired phylogeny using a dropdown menu (Fig. 1Bi; left). In userTree, a user selects a phylogeny in newick format from their local computer (Fig. 1Bi; right).

  2. 2.

    Selection of Taxa

    A user next uploads a text file containing the single-column list of taxa that they want a subtree for (Fig. 1Bii). Here, each taxon name must be identical to a taxon name in the full phylogeny.

  3. 3.

    Subtree output

    By clicking the ‘Update’ button, the user launches treehouse subtree retrieval. The subtree is plotted to the right of the side panel and buttons that allow the user to download a pdf or text file of the subtree are below it (Fig. 1Biii). Lastly, the full set of taxa in the currently uploaded treehouse phylogeny is listed (Fig. 1Bc; left).


Treehouse is a simple and powerful tool that facilitates subtree retrieval from large phylogenies.


Treehouse’s functionality rests on the performance of one task, namely removing taxa from a phylogeny. To the experienced phylogenetic or phylogenomic researcher, this might seem to be a trivial task but is not so for most users of phylogenetic trees and no other user-friendly methods are available. Thus, we anticipate the ‘typical’ treehouse users to be researchers that use phylogenies to form hypotheses but do not routinely infer phylogenies themselves. We also anticipate treehouse to be a useful teaching tool.

Availability of data and materials

All data, materials, and code are publically available at


  1. 1.

    Peter J, De Chiara M, Friedrich A, Yue J-X, Pflieger D, Bergström A, et al. Genome evolution across 1,011 Saccharomyces cerevisiae isolates. Nature. 2018;556:339–44.

    CAS  Article  Google Scholar 

  2. 2.

    Varga T, Krizsán K, Földi C, Dima B, Sánchez-García M, Sánchez-Ramírez S, et al. Megaphylogeny resolves global patterns of mushroom evolution. Nat Ecol Evol. 2019;3:668.

    PubMed  Google Scholar 

  3. 3.

    Hug LA, Baker BJ, Anantharaman K, Brown CT, Probst AJ, Castelle CJ, et al. A new view of the tree of life. Nat Microbiol. 2016;1:16048.

    CAS  Article  PubMed  Google Scholar 

  4. 4.

    Shen X-X, Opulente DA, Kominek J, Zhou X, Steenwyk JL, Buh KV, et al. Tempo and mode of genome evolution in the budding yeast subphylum. Cell. 2018;175(1533–1545):e20.

    Google Scholar 

  5. 5.

    Prum RO, Berv JS, Dornburg A, Field DJ, Townsend JP, Lemmon EM, et al. A comprehensive phylogeny of birds (Aves) using targeted next-generation DNA sequencing. Nature. 2015;526:569–73.

    CAS  Article  Google Scholar 

  6. 6.

    Jarvis ED, Mirarab S, Aberer AJ, Li B, Houde P, Li C, et al. Whole-genome analyses resolve early branches in the tree of life of modern birds. Science. 2014;346:1320–31.

    CAS  Article  Google Scholar 

  7. 7.

    Misof B, Liu S, Meusemann K, Peters RS, Donath A, Mayer C, et al. Phylogenomics resolves the timing and pattern of insect evolution. Science. 2014;346:763–7.

    CAS  Article  Google Scholar 

  8. 8.

    Song S, Liu L, Edwards SV, Wu S. Resolving conflict in eutherian mammal phylogeny using phylogenomics and the multispecies coalescent model. Proc Natl Acad Sci. 2012;109:14942–7.

    CAS  Article  Google Scholar 

  9. 9.

    Tarver JE, dos Reis M, Mirarab S, Moran RJ, Parker S, O’Reilly JE, et al. The interrelationships of placental mammals and the limits of phylogenetic inference. Genome Biol Evol. 2016;8:330–44.

    CAS  Article  Google Scholar 

  10. 10.

    Borowiec ML, Lee EK, Chiu JC, Plachetzki DC. Extracting phylogenetic signal and accounting for bias in whole-genome data sets supports the Ctenophora as sister to remaining Metazoa. BMC Genomics. 2015;16:987.

    Article  Google Scholar 

  11. 11.

    Whelan NV, Kocot KM, Moroz LL, Halanych KM. Error, signal, and the placement of Ctenophora sister to all other animals. Proc Natl Acad Sci. 2015;112:5773–8.

    CAS  Article  Google Scholar 

  12. 12.

    Chen M-Y, Liang D, Zhang P. Selecting question-specific genes to reduce incongruence in phylogenomics: a case study of jawed vertebrate backbone phylogeny. Syst Biol. 2015;64:1104–20.

    CAS  Article  Google Scholar 

  13. 13.

    Struck TH, Golombek A, Weigert A, Franke FA, Westheide W, Purschke G, et al. The evolution of annelids reveals two adaptive routes to the interstitial realm. Curr Biol. 2015;25:1993–9.

    CAS  Article  Google Scholar 

  14. 14.

    Steenwyk JL, Shen X-X, Lind AL, Goldman GH, Rokas A. A robust phylogenomic time tree for biotechnologically and medically important fungi in the genera Aspergillus and Penicillium. MBio. 2019;10:e00925.

    Article  Google Scholar 

  15. 15.

    Desjardins CA, Giamberardino C, Sykes SM, Yu C-H, Tenor JL, Chen Y, et al. Population genomics and the evolution of virulence in the fungal pathogen Cryptococcus neoformans. Genome Res. 2017;27:1207–19.

    CAS  Article  Google Scholar 

  16. 16.

    James TY, Kauff F, Schoch CL, Matheny PB, Hofstetter V, Cox CJ, et al. Reconstructing the early evolution of Fungi using a six-gene phylogeny. Nature. 2006;443:818–22.

    CAS  Article  Google Scholar 

  17. 17.

    Shen XX, Zhou X, Kominek J, Kurtzman CP, Hittinger CT, Rokas A. reconstructing the backbone of the Saccharomycotina yeast phylogeny using genome-scale data. G3 Genes|Genomes|Genetics. 2016;6:3927–39.

    Article  Google Scholar 

  18. 18.

    Yang Y, Moore MJ, Brockington SF, Soltis DE, Wong GKS, Carpenter EJ, et al. Dissecting molecular evolution in the highly diverse plant clade Caryophyllales using transcriptome sequencing. Mol Biol Evol. 2015;32:2001–14.

    CAS  Article  Google Scholar 

  19. 19.

    Xi Z, Liu L, Rest JS, Davis CC. Coalescent versus concatenation methods and the placement of Amborella as sister to Water Lilies. Syst Biol. 2014;63:919–32.

    Article  Google Scholar 

  20. 20.

    Wickett NJ, Mirarab S, Nguyen N, Warnow T, Carpenter E, Matasci N, et al. Phylotranscriptomic analysis of the origin and early diversification of land plants. Proc Natl Acad Sci. 2014;111:E4859–68.

    CAS  Article  Google Scholar 

  21. 21.

    Revell LJ. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol Evol. 2012;3:217–23.

    Article  Google Scholar 

  22. 22.

    Paradis E, Claude J, Strimmer K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics. 2004;20:289–90.

    CAS  Article  Google Scholar 

Download references


We thank members of the Rokas laboratory, and in particular Xing-Xing Shen, for helpful comments, discussion, and user feedback. We thank Christina Cuomo for providing useful user feedback. We thank the research community for their input on what phylogenies they would like to be part of the treehouse database.


JLS was supported by the Graduate Program in Biological Sciences at Vanderbilt University. AR was supported by the National Science Foundation (DEB-1442113), the Burroughs Wellcome Fund, and the Guggenheim Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information




JLS and AR conceived the research and wrote the article. JLS conducted the research and implemented treehouse in the R programming language. Both authors read and approved the final manuscript.

Corresponding author

Correspondence to Antonis Rokas.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Steenwyk, J.L., Rokas, A. Treehouse: a user-friendly application to obtain subtrees from large phylogenies. BMC Res Notes 12, 541 (2019).

Download citation


  • Phylogenomics
  • Phylogenetics
  • Big data
  • Tree
  • Tree pruning
  • Shiny
  • Graphical user interface