A comparison of the Mantel test with a generalised distance covariance test

Omelka, Marek; Hudecová, Šárka

doi:10.1002/env.2238

Cited by 22 publications

(18 citation statements)

References 25 publications

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“…Minas et al [69] show that the Mantel test is less powerful than the test based on the GRV coefficient (4.1) using simulations. In the same way, Omelka and Hudecová [75] underlined the superiority of the dCov test over the Mantel test. However, despite its widespread use, some of the properties of the Mantel test are unclear and recently its utility questioned [75].…”

Section: Beyond Euclidean Distancesmentioning

confidence: 85%

“…In the same way, Omelka and Hudecová [75] underlined the superiority of the dCov test over the Mantel test. However, despite its widespread use, some of the properties of the Mantel test are unclear and recently its utility questioned [75]. Legendre and Fortin [61] show that the Mantel coefficient is not equal to 0 when the covariance between the two sets of variables is null and thus can’t be used to detect linear relationships.…”

Section: Beyond Euclidean Distancesmentioning

confidence: 85%

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Measuring multivariate association and beyond

Josse

Holmes

2016

Statist. Surv.

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Simple correlation coefficients between two variables have been generalized to measure association between two matrices in many ways. Coefficients such as the RV coefficient, the distance covariance (dCov) coefficient and kernel based coefficients are being used by different research communities. Scientists use these coefficients to test whether two random vectors are linked. Once it has been ascertained that there is such association through testing, then a next step, often ignored, is to explore and uncover the association’s underlying patterns. This article provides a survey of various measures of dependence between random vectors and tests of independence and emphasizes the connections and differences between the various approaches. After providing definitions of the coefficients and associated tests, we present the recent improvements that enhance their statistical properties and ease of interpretation. We summarize multi-table approaches and provide scenarii where the indices can provide useful summaries of heterogeneous multi-block data. We illustrate these different strategies on several examples of real data and suggest directions for future research.

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Section: Beyond Euclidean Distancesmentioning

confidence: 85%

Section: Beyond Euclidean Distancesmentioning

confidence: 85%

Measuring multivariate association and beyond

Josse

Holmes

2016

Statist. Surv.

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“…In order to compare the three dissimilarity matrices arising from co-citation, editorial board and author networks for each discipline, we adopt the generalized distance correlation R d suggested by Omelka and Hudecová (2013) on the basis of the seminal proposal by Székely et al (2007). It should be remarked that such a correlation index avoids the drawbacks emphasized by Dutilleul et al (2000) when the classical Mantel coefficient is assumed instead (Omelka and Hudecova 2013 From the analysis of Table 1, the dependence between the considered dissimilarity matrices is apparent. Indeed, the observed values of √ R d are greater than (or nearly equal to) the value 0.5 for each combination of networks in the three disciplines.…”

Section: Dissimilarities Among Networkmentioning

confidence: 99%

Intellectual and social similarity among scholarly journals: An exploratory comparison of the networks of editors, authors and co-citations

Baccini

Barabesi

Khelfaoui

et al. 2020

Quantitative Science Studies

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This paper explores, by using suitable quantitative techniques, to what extent the intellectual proximity among scholarly journals is also a proximity in terms of social communities gathered around the journals. Three fields are considered: statistics, economics and information and library sciences. Co-citation networks (CC) represent the intellectual proximity among journals.The academic communities around the journals are represented by considering the networks of journals generated by authors writing in more than one journal (interlocking authorship: IA), and the networks generated by scholars sitting in the editorial board of more than one journal (interlocking editorship: IE). For comparing the whole structure of the networks, the dissimilarity matrices are considered. The CC, IE and IA networks appear to be correlated for the three fields. The strongest correlations is between CC and IA for the three fields. Lower and similar correlations are obtained for CC and IE, and for IE and IA. The CC, IE and IA networks are then partitioned in communities. Information and library sciences is the field where communities are more easily detectable, while the most difficult field is economics. The degrees of association among the detected communities show that they are not independent. For all the fields, the strongest association is between CC and IA networks; the minimum level of association is between IE and CC. Overall, these results indicate that the intellectual proximity is also a proximity among authors and among editors of the journals. Thus, the three maps of editorial power, intellectual proximity and authors communities tell similar stories.

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“…Distance matrices of resistance genes, 16S rRNA genes, and housekeeping genes sequences were calculated with Phylip 3.69 software [35]. Correlation analysis was based on generalized distance covariance test [41] based on the method developed by Szekely et al [42]. As the aim of the study is explanatory, no correction of p-values for multiple testing was used.…”

Section: Methodsmentioning

confidence: 99%

Phylogenetic relatedness determined between antibiotic resistance and 16S rRNA genes in actinobacteria

et al. 2015

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BackgroundDistribution and evolutionary history of resistance genes in environmental actinobacteria provide information on intensity of antibiosis and evolution of specific secondary metabolic pathways at a given site. To this day, actinobacteria producing biologically active compounds were isolated mostly from soil but only a limited range of soil environments were commonly sampled. Consequently, soil remains an unexplored environment in search for novel producers and related evolutionary questions.ResultsNinety actinobacteria strains isolated at contrasting soil sites were characterized phylogenetically by 16S rRNA gene, for presence of erm and ABC transporter resistance genes and antibiotic production. An analogous analysis was performed in silico with 246 and 31 strains from Integrated Microbial Genomes (JGI_IMG) database selected by the presence of ABC transporter genes and erm genes, respectively. In the isolates, distances of erm gene sequences were significantly correlated to phylogenetic distances based on 16S rRNA genes, while ABC transporter gene distances were not. The phylogenetic distance of isolates was significantly correlated to soil pH and organic matter content of isolation sites. In the analysis of JGI_IMG datasets the correlation between phylogeny of resistance genes and the strain phylogeny based on 16S rRNA genes or five housekeeping genes was observed for both the erm genes and ABC transporter genes in both actinobacteria and streptomycetes. However, in the analysis of sequences from genomes where both resistance genes occurred together the correlation was observed for both ABC transporter and erm genes in actinobacteria but in streptomycetes only in the erm gene.ConclusionsThe type of erm resistance gene sequences was influenced by linkage to 16S rRNA gene sequences and site characteristics. The phylogeny of ABC transporter gene was correlated to 16S rRNA genes mainly above the genus level. The results support the concept of new specific secondary metabolite scaffolds occurring more likely in taxonomically distant producers but suggest that the antibiotic selection of gene pools is also influenced by site conditions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12866-015-0416-6) contains supplementary material, which is available to authorized users.

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A comparison of the Mantel test with a generalised distance covariance test

Cited by 22 publications

References 25 publications

Measuring multivariate association and beyond

Measuring multivariate association and beyond

Intellectual and social similarity among scholarly journals: An exploratory comparison of the networks of editors, authors and co-citations

Phylogenetic relatedness determined between antibiotic resistance and 16S rRNA genes in actinobacteria

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