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  A guide to statistical analysis in microbial ecology: a community-focused, living review of multivariate data analyses

Buttigieg, P., & Ramette, A. (2014). A guide to statistical analysis in microbial ecology: a community-focused, living review of multivariate data analyses. FEMS Microbiology Ecology, 90(3): 1, pp. 543-550.

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Buttigieg14.pdf (Publisher version), 295KB
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Buttigieg, P.1, Author           
Ramette, A.1, Author           
Affiliations:
1HGF MPG Joint Research Group for Deep Sea Ecology & Technology, Max Planck Institute for Marine Microbiology, Max Planck Society, ou_2481702              

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 Abstract: The application of multivariate statistical analyses has become a consistent feature in microbial ecology. However, many microbial ecologists are still in the process of developing a deep understanding of these methods and appreciating their limitations. As a consequence, staying abreast of progress and debate in this arena poses an additional challenge to many microbial ecologists. To address these issues, we present the GUide to STatistical Analysis in Microbial Ecology (GUSTA ME): a dynamic, web-based resource providing accessible descriptions of numerous multivariate techniques relevant to microbial ecologists. A combination of interactive elements allows users to discover and navigate between methods relevant to their needs and examine how they have been used by others in the field. We have designed GUSTA ME to become a community-led and -curated service, which we hope will provide a common reference and forum to discuss and disseminate analytical techniques relevant to the microbial ecology community.

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Language(s): eng - English
 Dates: 2014-12
 Publication Status: Issued
 Pages: 8
 Publishing info: -
 Table of Contents: -
 Rev. Type: Internal
 Identifiers: eDoc: 700881
ISI: 000346057900001
 Degree: -

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Title: FEMS Microbiology Ecology
Source Genre: Journal
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Publ. Info: Amsterdam : Oxford University Press
Pages: - Volume / Issue: 90 (3) Sequence Number: 1 Start / End Page: 543 - 550 Identifier: ISSN: 0168-6496
CoNE: https://pure.mpg.de/cone/journals/resource/954925526820_1