References

Chapleur, Olivier, Céline Madigou, Raphaël Civade, Yohan Rodolphe, Laurent Mazéas, and Théodore Bouchez. 2016. “Increasing Concentrations of Phenol Progressively Affect Anaerobic Digestion of Cellulose and Associated Microbial Communities.” Biodegradation 27 (1): 15–27.

Duvallet, Claire, Sean M Gibbons, Thomas Gurry, Rafael A Irizarry, and Eric J Alm. 2017. “Meta-Analysis of Gut Microbiome Studies Identifies Disease-Specific and Shared Responses.” Nature Communications 8 (1): 1–10.

Fan, Yong, and Oluf Pedersen. 2020. “Gut Microbiota in Human Metabolic Health and Disease.” Nature Reviews Microbiology, 1–17.

Gibson, Glenn R, Hollie M Probert, Jan Van Loo, Robert A Rastall, and Marcel B Roberfroid. 2004. “Dietary Modulation of the Human Colonic Microbiota: Updating the Concept of Prebiotics.” Nutrition Research Reviews 17 (2): 259–75.

Haro, Carmen, Oriol A Rangel-Zúñiga, Juan F Alcalá-Dı́az, Francisco Gómez-Delgado, Pablo Pérez-Martı́nez, Javier Delgado-Lista, Gracia M Quintana-Navarro, et al. 2016. “Intestinal Microbiota Is Influenced by Gender and Body Mass Index.” PloS One 11 (5): e0154090.

Hawinkel, Stijn, Federico Mattiello, Luc Bijnens, and Olivier Thas. 2019. “A Broken Promise: Microbiome Differential Abundance Methods Do Not Control the False Discovery Rate.” Briefings in Bioinformatics 20 (1): 210–21.

Hieken, Tina J, Jun Chen, Tanya L Hoskin, Marina Walther-Antonio, Stephen Johnson, Sheri Ramaker, Jian Xiao, et al. 2016. “The Microbiome of Aseptically Collected Human Breast Tissue in Benign and Malignant Disease.” Scientific Reports 6: 30751.

Kim, Dorothy, Casey E Hofstaedter, Chunyu Zhao, Lisa Mattei, Ceylan Tanes, Erik Clarke, Abigail Lauder, et al. 2017. “Optimizing Methods and Dodging Pitfalls in Microbiome Research.” Microbiome 5 (1): 52.

Kong, Geraldine, Kim-Anh Lê Cao, Louise M Judd, ShanShan Li, Thibault Renoir, and Anthony J Hannan. 2020. “Microbiome Profiling Reveals Gut Dysbiosis in a Transgenic Mouse Model of Huntington’s Disease.” Neurobiology of Disease 135: 104268.

LÃŒdecke, Daniel, Dominique Makowski, Philip Waggoner, and Indrajeet Patil. 2020. “Performance: Assessment of Regression Models Performance.” CRAN. https://doi.org/10.5281/zenodo.3952174.

Leek, Jeffrey T, W Evan Johnson, Hilary S Parker, Andrew E Jaffe, and John D Storey. 2012. “The Sva Package for Removing Batch Effects and Other Unwanted Variation in High-Throughput Experiments.” Bioinformatics 28 (6): 882–83.

Lex, Alexander, Nils Gehlenborg, Hendrik Strobelt, Romain Vuillemot, and Hanspeter Pfister. 2014. “UpSet: Visualization of Intersecting Sets.” IEEE Transactions on Visualization and Computer Graphics 20 (12): 1983–92.

Lozupone, Catherine, Jesse Stombaugh, Antonio Gonzalez, Gail Ackermann, Doug Wendel, Yoshiki Vázquez-Baeza, Janet K Jansson, Jeffrey I Gordon, and Rob Knight. 2013. “Meta-Analyses of Studies of the Human Microbiota.” Genome Research, gr–151803.

Marchesi, Julian R, and Jacques Ravel. 2015. “The Vocabulary of Microbiome Research: A Proposal.” Springer.

McGregor, Kevin, Aurélie Labbe, and Celia MT Greenwood. 2020. “MDiNE: A Model to Estimate Differential Co-Occurrence Networks in Microbiome Studies.” Bioinformatics 36 (6): 1840–47.

McMurdie, Paul J, and Susan Holmes. 2014. “Waste Not, Want Not: Why Rarefying Microbiome Data Is Inadmissible.” PLoS Computational Biology 10 (4): e1003531.

Moskovicz, Veronica, Rina Ben-El, Guy Horev, and Boaz Mizrahi. 2020. “Skin Microbiota Dynamics Following b. Subtilis Formulation Challenge.”

Nakagawa, Shinichi, and Holger Schielzeth. 2013. “A General and Simple Method for Obtaining R2 from Generalized Linear Mixed-Effects Models.” Methods in Ecology and Evolution 4 (2): 133–42.

Poirier, Simon, Sébastien Déjean, Cédric Midoux, Kim-Anh Lê Cao, and Olivier Chapleur. 2020. “Integrating Independent Microbial Studies to Build Predictive Models of Anaerobic Digestion Inhibition by Ammonia and Phenol.” Bioresource Technology 316: 123952.

Quinn, Thomas P, Ionas Erb, Mark F Richardson, and Tamsyn M Crowley. 2018. “Understanding Sequencing Data as Compositions: An Outlook and Review.” Bioinformatics 34 (16): 2870–78.

Ray, Prasun, Venkatachalam Lakshmanan, Jessy L Labbé, and Kelly D Craven. 2020. “Microbe to Microbiome: A Paradigm Shift in the Application of Microorganisms for Sustainable Agriculture.” Frontiers in Microbiology 11: 3323.

Rohart, Florian, Benoı̂t Gautier, Amrit Singh, and Kim-Anh Lê Cao. 2017. “mixOmics: An r Package for ‘Omics Feature Selection and Multiple Data Integration.” PLoS Computational Biology 13 (11): e1005752.

Sacristán-Soriano, Oriol, Bernard Banaigs, Emilio O Casamayor, and Mikel A Becerro. 2011. “Exploring the Links Between Natural Products and Bacterial Assemblages in the Sponge Aplysina Aerophoba.” Appl. Environ. Microbiol. 77 (3): 862–70.

Singh, Amrit, Casey P Shannon, Benoı̂t Gautier, Florian Rohart, Michaël Vacher, Scott J Tebbutt, and Kim-Anh Lê Cao. 2019. “DIABLO: An Integrative Approach for Identifying Key Molecular Drivers from Multi-Omics Assays.” Bioinformatics 35 (17): 3055–62.

Susin, Antoni, Yiwen Wang, Kim-Anh Lê Cao, and M Luz Calle. 2020. “Variable Selection in Microbiome Compositional Data Analysis.” NAR Genomics and Bioinformatics 2 (2): lqaa029.

Wang, Charlotte H, Linda Wu, Zengyan Wang, Magdy S Alabady, Daniel Parson, Zainab Molumo, and Sarah C Fankhauser. 2020. “Characterizing Changes in Soil Microbiome Abundance and Diversity Due to Different Cover Crop Techniques.” PloS One 15 (5): e0232453.

Wang, Yiwen, and Kim-Anh Lê Cao. 2020. “A Multivariate Method to Correct for Batch Effects in Microbiome Data.” bioRxiv.

Wang, Yiwen, and Kim-Anh LêCao. 2020. “Managing Batch Effects in Microbiome Data.” Briefings in Bioinformatics 21 (6): 1954–70.

Weiss, Sophie, Zhenjiang Zech Xu, Shyamal Peddada, Amnon Amir, Kyle Bittinger, Antonio Gonzalez, Catherine Lozupone, et al. 2017. “Normalization and Microbial Differential Abundance Strategies Depend Upon Data Characteristics.” Microbiome 5 (1): 1–18.