Dataset Information

Measuring nestedness: A comparative study of the performance of different metrics.

ABSTRACT: Nestedness is a property of interaction networks widely observed in natural mutualistic communities, among other systems. A perfectly nested network is characterized by the peculiarity that the interactions of any node form a subset of the interactions of all nodes with higher degree. Despite a widespread interest on this pattern, no general consensus exists on how to measure it. Instead, several nestedness metrics, based on different but not necessarily independent properties of the networks, coexist in the literature, blurring the comparison between ecosystems. In this work, we present a detailed critical study of the behavior of six nestedness metrics and the variants of two of them. In order to evaluate their performance, we compare the obtained values of the nestedness of a large set of real networks among them and against a maximum-entropy and maximum-likelihood null model. We also analyze the dependencies of each metrics on different network parameters, as size, fill, and eccentricity. Our results point out, first, that the metrics do not rank networks universally in terms of their degree of nestedness. Furthermore, several metrics show significant dependencies on the network properties considered. The study of these dependencies allows us to understand some of the observed systematic shifts against the null model. Altogether, this paper intends to provide readers with a critical guide on how to measure nestedness patterns, by explaining the functioning of several metrics and disclosing their qualities and flaws. Besides, we also aim to extend the application of null models based on maximum entropy to the scarcely explored area of ecological networks. Finally, we provide a fully documented repository that allows constructing the null model and calculating the studied nestedness indexes. In addition, it provides the probability matrices to build the null model for a large dataset of more than 200 bipartite networks.

SUBMITTER: Payrato-Borras C

PROVIDER: S-EPMC7663079 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Measuring nestedness: A comparative study of the performance of different metrics.

Payrató-Borràs Clàudia C Hernández Laura L Moreno Yamir Y

Ecology and evolution 20201022 21

Nestedness is a property of interaction networks widely observed in natural mutualistic communities, among other systems. A perfectly nested network is characterized by the peculiarity that the interactions of any node form a subset of the interactions of all nodes with higher degree. Despite a widespread interest on this pattern, no general consensus exists on how to measure it. Instead, several nestedness metrics, based on different but not necessarily independent properties of the networks, c ...[more]

PMID: 33209259

Similar Datasets

Project description:Reliable detection of mecA and mecC-mediated beta-lactam resistance using automated antimicrobial susceptibility test systems is critical for patient care. The aim of this study was to compare the performance of the new cefoxitin screen test (oxsf02n) on the Vitek 2 card (Vitek 2) and BD Phoenix PMC-100 Gram-Positive AST Panel (Phoenix) against the reference method for the detection of mecA (and mecC)-mediated beta-lactam resistance. Two hundred fifty clinical fresh and stock Staphylococcus spp. isolates were included. There were 120 mecA-positive, 10 mecC-positive, and 120 mecA and mecC-negative isolates. Cefoxitin screen and oxacillin tests were performed on Vitek 2 and Phoenix and by their respective reference methods (disk diffusion for the cefoxitin screen test and broth microdilution for oxacillin) for all isolates. PCR testing was also performed to confirm the presence of mecA and/or mecC genes. Results from each system were compared to the reference methods. Statistical hypotheses were evaluated both for Vitek 2 compared to the reference methods and Vitek 2 compared to the Phoenix. Compared to the reference method, the Vitek 2 cefoxitin screen test had 100% sensitivity/98% specificity and the Phoenix cefoxitin screen test had 84% sensitivity/100% specificity for the detection of mecA (and mecC)-mediated beta-lactam resistance. When the oxacillin test was combined with the cefoxitin screen for Vitek 2, the sensitivity and specificity were unchanged. However, when the oxacillin and cefoxitin screen tests were combined for the Phoenix, the sensitivity increased to 100% and the specificity remained unchanged (100%). When considering cefoxitin alone, the Vitek 2 screen test showed a higher sensitivity than the Phoenix for the detection of mecA and mecC-mediated beta-lactam resistance. However, currently, both systems use a combination of the cefoxitin and oxacillin tests to interpret the final result, and both reached a high level of performance when cefoxitin and oxacillin results were combined.IMPORTANCEThis research marks the inaugural evaluation of the revamped cefoxitin screen test version in Vitek 2, juxtaposing it against reference methods and a primary competitor BD Phoenix.

Dataset Information

Measuring nestedness: A comparative study of the performance of different metrics.

Publications

Measuring nestedness: A comparative study of the performance of different metrics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets