mSystems (Apr 2021)
EMPress Enables Tree-Guided, Interactive, and Exploratory Analyses of Multi-omic Data Sets
- Kalen Cantrell,
- Marcus W. Fedarko,
- Gibraan Rahman,
- Daniel McDonald,
- Yimeng Yang,
- Thant Zaw,
- Antonio Gonzalez,
- Stefan Janssen,
- Mehrbod Estaki,
- Niina Haiminen,
- Kristen L. Beck,
- Qiyun Zhu,
- Erfan Sayyari,
- James T. Morton,
- George Armstrong,
- Anupriya Tripathi,
- Julia M. Gauglitz,
- Clarisse Marotz,
- Nathaniel L. Matteson,
- Cameron Martino,
- Jon G. Sanders,
- Anna Paola Carrieri,
- Se Jin Song,
- Austin D. Swafford,
- Pieter C. Dorrestein,
- Kristian G. Andersen,
- Laxmi Parida,
- Ho-Cheol Kim,
- Yoshiki Vázquez-Baeza,
- Rob Knight
Affiliations
- Kalen Cantrell
- Department of Computer Science, Jacobs School of Engineering, University of California, San Diego, California, USA
- Marcus W. Fedarko
- Department of Computer Science, Jacobs School of Engineering, University of California, San Diego, California, USA
- Gibraan Rahman
- Bioinformatics and Systems Biology Program, University of California, San Diego, California, USA
- Daniel McDonald
- Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA
- Yimeng Yang
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA
- Thant Zaw
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA
- Antonio Gonzalez
- Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA
- Stefan Janssen
- Algorithmic Bioinformatics, Justus Liebig University, Giessen, Germany
- Mehrbod Estaki
- Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA
- Niina Haiminen
- IBM T. J. Watson Research Center, Yorktown Heights, New York, USA
- Kristen L. Beck
- IBM Almaden Research Center, San Jose, California, USA
- Qiyun Zhu
- Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA
- Erfan Sayyari
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA
- James T. Morton
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, New York, USA
- George Armstrong
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA
- Anupriya Tripathi
- Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA
- Julia M. Gauglitz
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, California, USA
- Clarisse Marotz
- Department of Pediatrics, School of Medicine, University of California, San Diego, California, USA
- Nathaniel L. Matteson
- Scripps Research Institute, San Diego, California, USA
- Cameron Martino
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA
- Jon G. Sanders
- Cornell Institute for Host-Microbe Interaction and Disease, Cornell University, Ithaca, New York, USA
- Anna Paola Carrieri
- IBM Research, The Hartree Centre, Daresbury, United Kingdom
- Se Jin Song
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA
- Austin D. Swafford
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA
- Pieter C. Dorrestein
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA
- Kristian G. Andersen
- Scripps Research Institute, San Diego, California, USA
- Laxmi Parida
- IBM T. J. Watson Research Center, Yorktown Heights, New York, USA
- Ho-Cheol Kim
- IBM Almaden Research Center, San Jose, California, USA
- Yoshiki Vázquez-Baeza
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California, San Diego, California, USA
- Rob Knight
- Department of Computer Science, Jacobs School of Engineering, University of California, San Diego, California, USA
- DOI
- https://doi.org/10.1128/msystems.01216-20
- Journal volume & issue
-
Vol. 6,
no. 2
Abstract
ABSTRACT Standard workflows for analyzing microbiomes often include the creation and curation of phylogenetic trees. Here we present EMPress, an interactive web tool for visualizing trees in the context of microbiome, metabolome, and other community data scalable to trees with well over 500,000 nodes. EMPress provides novel functionality—including ordination integration and animations—alongside many standard tree visualization features and thus simplifies exploratory analyses of many forms of ‘omic data. IMPORTANCE Phylogenetic trees are integral data structures for the analysis of microbial communities. Recent work has also shown the utility of trees constructed from certain metabolomic data sets, further highlighting their importance in microbiome research. The ever-growing scale of modern microbiome surveys has led to numerous challenges in visualizing these data. In this paper we used five diverse data sets to showcase the versatility and scalability of EMPress, an interactive web visualization tool. EMPress addresses the growing need for exploratory analysis tools that can accommodate large, complex multi-omic data sets.
Keywords
