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Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution.

ABSTRACT: Geometric morphometrics aims to characterize of the geometry of complex traits. It is therefore by essence multivariate. The most popular methods to investigate patterns of differentiation in this context are (1) the Principal Component Analysis (PCA), which is an eigenvalue decomposition of the total variance-covariance matrix among all specimens; (2) the Canonical Variate Analysis (CVA, a.k.a. linear discriminant analysis (LDA) for more than two groups), which aims at separating the groups by maximizing the between-group to within-group variance ratio; (3) the between-group PCA (bgPCA) which investigates patterns of between-group variation, without standardizing by the within-group variance. Standardizing within-group variance, as performed in the CVA, distorts the relationships among groups, an effect that is particularly strong if the variance is similarly oriented in a comparable way in all groups. Such shared direction of main morphological variance may occur and have a biological meaning, for instance corresponding to the most frequent standing genetic variation in a population. Here we undertake a case study of the evolution of house mouse molar shape across various islands, based on the real dataset and simulations. We investigated how patterns of main variance influence the depiction of among-group differentiation according to the interpretation of the PCA, bgPCA and CVA. Without arguing about a method performing 'better' than another, it rather emerges that working on the total or between-group variance (PCA and bgPCA) will tend to put the focus on the role of direction of main variance as line of least resistance to evolution. Standardizing by the within-group variance (CVA), by dampening the expression of this line of least resistance, has the potential to reveal other relevant patterns of differentiation that may otherwise be blurred.

SUBMITTER: Renaud S

PROVIDER: S-EPMC4507858 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution.

Renaud Sabrina S Dufour Anne-Béatrice AB Hardouin Emilie A EA Ledevin Ronan R Auffray Jean-Christophe JC

PloS one 20150720 7

Geometric morphometrics aims to characterize of the geometry of complex traits. It is therefore by essence multivariate. The most popular methods to investigate patterns of differentiation in this context are (1) the Principal Component Analysis (PCA), which is an eigenvalue decomposition of the total variance-covariance matrix among all specimens; (2) the Canonical Variate Analysis (CVA, a.k.a. linear discriminant analysis (LDA) for more than two groups), which aims at separating the groups by ...[more]

PMID: 26192946

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Project description:ObjectivesPeople increasingly search for health information through the media and make decisions about their health based on these health stories. The mainstream media, including newspapers, are often the first source for the public to obtain health information. This study aims to assess the health stories reported in the health edition of People's Daily in 2019 with four tools of the Media Doctor Toolkit (MDT), which can be an effective tool to evaluate the quality of public health stories. Based on the results, we attempt to address the gap in media coverage in terms of reporting on public health issues, and promote media to display the image of medical staff objectively, both of which can improve relationship of doctors, nurses and patients.MethodsA prospective quantitative analysis of the quality of health stories reported in the health edition of People's Daily from 1 February to September 31, 2019 was conducted. Forty-eight articles were collected and divided into four groups according to the MDT standards. Four rating tools were adapted from the MDT to assess the quality of the groups with corresponding criteria.ResultsForty-eight unique health stories were assessed with four MDT rating tools. The mean total satisfactory score was 80%. Health advice had the highest average satisfactory score, 84%, compared with health policy group and public health problems and their solutions, at 80% and 77%, respectively. Health news group had the lowest score at 73%.ConclusionThis study provides a description of the quality of health stories on People's Daily. The overall quality of People's Daily was fairly good, although there was a wide range of quality between groups. The health edition of People's Daily covers a wide range of health topics such as new medical methods, doctor-patient relationship, advanced nursing practice, lifestyle change of health promotion etc. which promote excellence in providing the latest health information, representing medical staff image, resolve the disharmonious factors in the relationship between doctors and patients, and creating a good medical environment for the public. The findings of this study also provide insight into problems in health reporting of People's Daily.

Dataset Information

Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution.

Publications

Once upon Multivariate Analyses: When They Tell Several Stories about Biological Evolution.

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