Microbiome-Friday-2023-09-08

In this repository, you will find the references used in my presentation for the Microbiome Friday. The title of my presentation is The data essence is not invisible to the eyes: exploring microbiome data through the lens of model-based approaches. The references stored here provide further reading and support for the concepts discussed in my presentation. In addition to the references, I also included links to tutorials for the methods I discussed in my presentation. I hope to make it easier for you to apply the model-based approaches for analysis of -omics data. The Petit Prince's analogy was originally presented by Susan Holmes in a talk available online in the YouTube channel of IPAM and inspired this presentation.

References (in order of appearance)

Jia, Dini-Andreote, Salles. ISME COMMUN. 2, 96 (2022) - Jia, X., Dini-Andreote, F. & Salles, J.F. Unravelling the interplay of ecological processes structuring the bacterial rare biosphere. ISME COMMUN. 2, 96 (2022). https://doi.org/10.1038/s43705-022-00177-6

McLaren, Willis, Callahan. Elife. 2019 - Michael R McLaren, Amy D Willis, Benjamin J Callahan (2019) Consistent and correctable bias in metagenomic sequencing experiments eLife 8:e46923 https://doi.org/10.7554/eLife.46923

McLaren et al. biorxiv. 2022 - Michael R. McLaren, Jacob T. Nearing, Amy D. Willis, Karen G. Lloyd, Benjamin J. Callahan bioRxiv 2022.08.19.504330; doi: https://doi.org/10.1101/2022.08.19.504330

Dimitrov et al. PeerJ. 2017 - Dimitrov, Mauricio R., et al. "Successive DNA extractions improve characterization of soil microbial communities." PeerJ 5 (2017): e2915.

Willis & Martin. Biostatistics. 2022 - Amy D Willis, Bryan D Martin, Estimating diversity in networked ecological communities, Biostatistics, Volume 23, Issue 1, January 2022, Pages 207–222, https://doi.org/10.1093/biostatistics/kxaa015

Manor & Borenstein. Genome Biology. 2015 - Manor, O., Borenstein, E. MUSiCC: a marker genes based framework for metagenomic normalization and accurate profiling of gene abundances in the microbiome. Genome Biol 16, 53 (2015). https://doi.org/10.1186/s13059-015-0610-8

Mardis. Annu. Rev. Genom. Human Genet. 2008 - Mardis ER. Next-generation DNA sequencing methods. Annu Rev Genomics Hum Genet. 2008;9:387-402. doi: 10.1146/annurev.genom.9.081307.164359. PMID: 18576944.

Gloor & Reid. Can. J. Microbiol. 2016 - Gregory B. Gloor and Gregor Reid. Compositional analysis: a valid approach to analyze microbiome high-throughput sequencing data. Canadian Journal of Microbiology. 62(8): 692-703. https://doi.org/10.1139/cjm-2015-0821

Leite & Kuramae. SBB. 2020 - Leite, Márcio FA, and Eiko E. Kuramae. "You must choose, but choose wisely: Model-based approaches for microbial community analysis." Soil Biology and Biochemistry 151 (2020): 108042. https://doi.org/10.1016/j.soilbio.2020.108042

Warton et al. Methods Ecol. Evol. 2012 - Warton, David I., Stephen T. Wright, and Yi Wang. "Distance‐based multivariate analyses confound location and dispersion effects." Methods in Ecology and Evolution 3.1 (2012): 89-101.

Warton & Hui. Methods Ecol. Evol. 2017 - Warton, David I., and Francis KC Hui. "The central role of mean‐variance relationships in the analysis of multivariate abundance data: A response to Roberts (2017)." Methods in Ecology and Evolution 8.11 (2017): 1408-1414. https://doi.org/10.1111/2041-210X.12843

Warton et al. TREE. 2015 - Warton DI, Blanchet FG, O'Hara RB, Ovaskainen O, Taskinen S, Walker SC, Hui FKC. So Many Variables: Joint Modeling in Community Ecology. Trends Ecol Evol. 2015 Dec;30(12):766-779. doi: 10.1016/j.tree.2015.09.007. Epub 2015 Oct 28. PMID: 26519235.

Ovaskainen et al. Ecol. 2017 - Ovaskainen, Otso, et al. "How to make more out of community data? A conceptual framework and its implementation as models and software." Ecology letters 20.5 (2017): 561-576. https://doi.org/10.1111/ele.12757

Zhou et al. Environ. microbiome. 2021 - Zhou, X., Leite, M.F.A., Zhang, Z. et al. Facilitation in the soil microbiome does not necessarily lead to niche expansion. Environmental Microbiome 16, 4 (2021). https://doi.org/10.1186/s40793-021-00373-2

Clark et al. Ecol. Monogr. 2017 - Clark, James S., et al. "Generalized joint attribute modeling for biodiversity analysis: Median‐zero, multivariate, multifarious data." Ecological Monographs 87.1 (2017): 34-56. https://doi.org/10.1002/ecm.1241

Bossolani et al. SBB. 2021 - Bossolani, João W., et al. "Modulation of the soil microbiome by long-term Ca-based soil amendments boosts soil organic carbon and physicochemical quality in a tropical no-till crop rotation system." Soil Biology and Biochemistry 156 (2021): 108188. https://doi.org/10.1016/j.soilbio.2021.108188