title: Correlation detection strategies in microbial data sets vary widely in sensitivity and precision.
abstract: Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques.
authors.affiliation: Department of Chemical and Biological Engineering, University of Colorado at Boulder, Boulder, CO, USA.
authors.forename: Sophie
authors.initials: S
authors.lastname: Weiss
authors.affiliation: BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO, USA.
authors.forename: Will
authors.initials: W
authors.lastname: Van Treuren
authors.affiliation: Department of Medicine, University of Colorado, Denver, CO, USA.
authors.forename: Catherine
authors.identifier: 0000-0003-4786-7202
authors.initials: C
authors.lastname: Lozupone
authors.affiliation: Department of Microbiology and Immunology, Rega Institute KU Leuven, Leuven, Belgium.|VIB Center for the Biology of Disease, VIB, Leuven, Belgium.|Laboratory of Microbiology, Vrije Universiteit Brussel, Brussels, Belgium.
authors.forename: Karoline
authors.identifier: 0000-0001-7129-2803
authors.initials: K
authors.lastname: Faust
authors.affiliation: Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Friedman
authors.affiliation: CAS Key Laboratory of Environmental Biotechnology, Chinese Academy of Sciences, Beijing, China.|Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA.
authors.forename: Ye
authors.identifier: 0000-0002-7584-0632
authors.initials: Y
authors.lastname: Deng
authors.affiliation: Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.|Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA.
authors.forename: Li Charlie
authors.identifier: 0000-0003-0868-1923
authors.initials: LC
authors.lastname: Xia
authors.affiliation: Departments of Pediatrics, University of California San Diego, La Jolla, CA, USA.
authors.forename: Zhenjiang Zech
authors.initials: ZZ
authors.lastname: Xu
authors.affiliation: Biota Technology, Inc., Denver, CO, USA.
authors.forename: Luke
authors.initials: L
authors.lastname: Ursell
authors.affiliation: Center for Microbiome Informatics and Therapeutics, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Eric J
authors.initials: EJ
authors.lastname: Alm
authors.affiliation: Center for Computational Biology and Bioinformatics, Department of Medicine, University of California San Diego, La Jolla, CA, USA.
authors.forename: Amanda
authors.initials: A
authors.lastname: Birmingham
authors.affiliation: Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
authors.forename: Jacob A
authors.initials: JA
authors.lastname: Cram
authors.affiliation: Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
authors.forename: Jed A
authors.identifier: 0000-0002-2361-1985
authors.initials: JA
authors.lastname: Fuhrman
authors.affiliation: Department of Microbiology and Immunology, Rega Institute KU Leuven, Leuven, Belgium.|VIB Center for the Biology of Disease, VIB, Leuven, Belgium.|Laboratory of Microbiology, Vrije Universiteit Brussel, Brussels, Belgium.
authors.forename: Jeroen
authors.initials: J
authors.lastname: Raes
authors.affiliation: Molecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA.
authors.forename: Fengzhu
authors.initials: F
authors.lastname: Sun
authors.affiliation: Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA.|Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA.|State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China.
authors.forename: Jizhong
authors.initials: J
authors.lastname: Zhou
authors.affiliation: Departments of Pediatrics, University of California San Diego, La Jolla, CA, USA.|Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.
authors.forename: Rob
authors.identifier: 0000-0002-0975-9019
authors.initials: R
authors.lastname: Knight
mesh_terms: D001419:Bacteria / Q000235:genetics*; D019985:Benchmarking / Q000706:statistics & numerical data*; D019295:Computational Biology; D006801:Humans; D056265:Microbial Interactions; D064307:Microbiota; D015233:Models, Statistical; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D013223:Statistics as Topic
chemical_list: D012336:RNA, Ribosomal, 16S