MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package

dc.citation.articleNumber301en_US
dc.citation.issueNumber1en_US
dc.citation.journalTitleBMC Bioinformaticsen_US
dc.citation.volumeNumber21en_US
dc.contributor.authorKoslovsky, Matthew D.en_US
dc.contributor.authorVannucci, Marinaen_US
dc.date.accessioned2020-08-14T20:13:37Zen_US
dc.date.available2020-08-14T20:13:37Zen_US
dc.date.issued2020en_US
dc.description.abstractUnderstanding the relation between the human microbiome and modulating factors, such as diet, may help researchers design intervention strategies that promote and maintain healthy microbial communities. Numerous analytical tools are available to help identify these relations, oftentimes via automated variable selection methods. However, available tools frequently ignore evolutionary relations among microbial taxa, potential relations between modulating factors, as well as model selection uncertainty.en_US
dc.identifier.citationKoslovsky, Matthew D. and Vannucci, Marina. "MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package." <i>BMC Bioinformatics,</i> 21, no. 1 (2020) Springer Nature: https://doi.org/10.1186/s12859-020-03640-0.en_US
dc.identifier.doihttps://doi.org/10.1186/s12859-020-03640-0en_US
dc.identifier.urihttps://hdl.handle.net/1911/109220en_US
dc.language.isoengen_US
dc.publisherSpringer Natureen_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleMicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R packageen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
MicroBVS.pdf
Size:
2.02 MB
Format:
Adobe Portable Document Format
Description: