Correlation detection strategies in microbial data sets vary widely in sensitivity and precision

• Published in: The ISME Journal Vol. 10; no. 7; pp. 1669 - 1681
• Main Authors: Weiss, Sophie, Van Treuren, Will, Lozupone, Catherine, Faust, Karoline, Friedman, Jonathan, Deng, Ye, Xia, Li Charlie, Xu, Zhenjiang Zech, Ursell, Luke, Alm, Eric J, Birmingham, Amanda, Cram, Jacob A, Fuhrman, Jed A, Raes, Jeroen, Sun, Fengzhu, Zhou, Jizhong, Knight, Rob
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01-07-2016; Nature Publishing Group
• Subjects: 101/47; 45; 631/326/2565/2134; 631/326/41/2142; Bacteria - genetics; Benchmarking - statistics & numerical data; Biomedical and Life Sciences; Computational Biology; Ecology; Evolutionary Biology; Humans; Life Sciences; Microbial activity; Microbial Ecology; Microbial Genetics and Genomics; Microbial Interactions; Microbiology; Microbiota; Models, Statistical; Original; original-article; RNA, Ribosomal, 16S - genetics; Statistics as Topic
• ISSN: 1751-7362; 1751-7370
• DOI: 10.1038/ismej.2015.235

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.