Multivariate Cutoff Level Analysis (MultiCoLA) of large community data sets

Gobet, A.; Quince, C.; Ramette, Alban Nicolas (2010). Multivariate Cutoff Level Analysis (MultiCoLA) of large community data sets. Nucleic acids research, 38(15), e155. Oxford University Press 10.1093/nar/gkq545

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High-throughput sequencing techniques are becoming attractive to molecular biologists and ecologists as they provide a time- and cost-effective way to explore diversity patterns in environmental samples at an unprecedented resolution. An issue common to many studies is the definition of what fractions of a data set should be considered as rare or dominant. Yet this question has neither been satisfactorily addressed, nor is the impact of such definition on data set structure and interpretation been fully evaluated. Here we propose a strategy, MultiCoLA ( Multi variate C ut o ff L evel A nalysis), to systematically assess the impact of various abundance or rarity cutoff levels on the resulting data set structure and on the consistency of the further ecological interpretation. We applied MultiCoLA to a 454 massively parallel tag sequencing data set of V6 ribosomal sequences from marine microbes in temperate coastal sands. Consistent ecological patterns were maintained after removing up to 35–40% rare sequences and similar patterns of beta diversity were observed after denoising the data set by using a preclustering algorithm of 454 flowgrams. This example validates the importance of exploring the impact of the definition of rarity in large community data sets. Future applications can be foreseen for data sets from different types of habitats, e.g. other marine environments, soil and human microbiota.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Service Sector > Institute for Infectious Diseases
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine

UniBE Contributor:

Ramette, Alban Nicolas

Subjects:

500 Science > 570 Life sciences; biology
300 Social sciences, sociology & anthropology > 360 Social problems & social services
600 Technology > 610 Medicine & health

ISSN:

0305-1048

Publisher:

Oxford University Press

Language:

English

Submitter:

Alban Nicolas Ramette

Date Deposited:

16 Mar 2017 14:21

Last Modified:

17 Mar 2017 22:39

Publisher DOI:

10.1093/nar/gkq545

PubMed ID:

20547594

BORIS DOI:

10.7892/boris.91401

URI:

https://boris.unibe.ch/id/eprint/91401

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