{"title":"Procrustes的形状不能一次分析、解释或可视化一个地标","authors":"Andrea Cardini, Verderame Adolfo Marco","doi":"10.1007/s11692-022-09565-1","DOIUrl":null,"url":null,"abstract":"<p>Landmark-based geometric morphometrics using the Procrustes approach has become the dominant family of methods in morphometrics. However, the superimposition (and sliding, if semilandmarks are present), that transforms raw coordinates into shape coordinates is biologically arbitrary. Procrustes has desirable statistical properties, but is not based on a biological model. The same is true for sliding methods. These techniques allow powerful statistical analyses of a full set of shape coordinates, but make the use of subsets of landmarks/semilandmarks problematic, inaccurate and misleading, if not totally wrong. Crucially, the biological arbitrariness of the superimposition prevents any meaningful quantification, analysis and interpretation of variation one landmark/semilandmark at a time. We exemplify how misleading this type of analyses can be by using a real dataset, as well as simulated data with isotropic variation. Both show inconsistencies in ‘per-landmark/semilandmark’ variances. The simulation in fact helps to make even more obvious that the pattern of variance is strongly influenced by the biologically arbitrary choice of the mathematical treatment. Unfortunately, despite this limitation of all superimposition methods being known since the early days of Procrustean morphometrics, there has been a recent series of papers in leading journals presenting results of ‘per-landmark’ analyses. Thus, we further clarify why these analyses are wrong and represent misleading examples that should not be followed: Procrustes shape data cannot be analyzed, visualized or interpreted one landmark at a time. For users who are in doubt, in the Conclusions, we provide a short list of recommendations on how to easily avoid this type of mistakes.</p>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Procrustes Shape Cannot be Analyzed, Interpreted or Visualized one Landmark at a Time\",\"authors\":\"Andrea Cardini, Verderame Adolfo Marco\",\"doi\":\"10.1007/s11692-022-09565-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Landmark-based geometric morphometrics using the Procrustes approach has become the dominant family of methods in morphometrics. However, the superimposition (and sliding, if semilandmarks are present), that transforms raw coordinates into shape coordinates is biologically arbitrary. Procrustes has desirable statistical properties, but is not based on a biological model. The same is true for sliding methods. These techniques allow powerful statistical analyses of a full set of shape coordinates, but make the use of subsets of landmarks/semilandmarks problematic, inaccurate and misleading, if not totally wrong. Crucially, the biological arbitrariness of the superimposition prevents any meaningful quantification, analysis and interpretation of variation one landmark/semilandmark at a time. We exemplify how misleading this type of analyses can be by using a real dataset, as well as simulated data with isotropic variation. Both show inconsistencies in ‘per-landmark/semilandmark’ variances. The simulation in fact helps to make even more obvious that the pattern of variance is strongly influenced by the biologically arbitrary choice of the mathematical treatment. Unfortunately, despite this limitation of all superimposition methods being known since the early days of Procrustean morphometrics, there has been a recent series of papers in leading journals presenting results of ‘per-landmark’ analyses. Thus, we further clarify why these analyses are wrong and represent misleading examples that should not be followed: Procrustes shape data cannot be analyzed, visualized or interpreted one landmark at a time. For users who are in doubt, in the Conclusions, we provide a short list of recommendations on how to easily avoid this type of mistakes.</p>\",\"PeriodicalId\":1,\"journal\":{\"name\":\"Accounts of Chemical Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":16.4000,\"publicationDate\":\"2022-03-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of Chemical Research\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1007/s11692-022-09565-1\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s11692-022-09565-1","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Procrustes Shape Cannot be Analyzed, Interpreted or Visualized one Landmark at a Time
Landmark-based geometric morphometrics using the Procrustes approach has become the dominant family of methods in morphometrics. However, the superimposition (and sliding, if semilandmarks are present), that transforms raw coordinates into shape coordinates is biologically arbitrary. Procrustes has desirable statistical properties, but is not based on a biological model. The same is true for sliding methods. These techniques allow powerful statistical analyses of a full set of shape coordinates, but make the use of subsets of landmarks/semilandmarks problematic, inaccurate and misleading, if not totally wrong. Crucially, the biological arbitrariness of the superimposition prevents any meaningful quantification, analysis and interpretation of variation one landmark/semilandmark at a time. We exemplify how misleading this type of analyses can be by using a real dataset, as well as simulated data with isotropic variation. Both show inconsistencies in ‘per-landmark/semilandmark’ variances. The simulation in fact helps to make even more obvious that the pattern of variance is strongly influenced by the biologically arbitrary choice of the mathematical treatment. Unfortunately, despite this limitation of all superimposition methods being known since the early days of Procrustean morphometrics, there has been a recent series of papers in leading journals presenting results of ‘per-landmark’ analyses. Thus, we further clarify why these analyses are wrong and represent misleading examples that should not be followed: Procrustes shape data cannot be analyzed, visualized or interpreted one landmark at a time. For users who are in doubt, in the Conclusions, we provide a short list of recommendations on how to easily avoid this type of mistakes.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.