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Titolo:
A generalized permutation model for the analysis of cross-species data
Autore:
Lapointe, FJ; Garland, T;
Indirizzi:
Univ Montreal, Dept Sci Biol, Montreal, PQ H3C 3J7, Canada Univ Montreal Montreal PQ Canada H3C 3J7 ol, Montreal, PQ H3C 3J7, Canada Univ Wisconsin, Dept Zool, Madison, WI 53706 USA Univ Wisconsin Madison WI USA 53706 sin, Dept Zool, Madison, WI 53706 USA
Titolo Testata:
JOURNAL OF CLASSIFICATION
fascicolo: 1, volume: 18, anno: 2001,
pagine: 109 - 127
SICI:
0176-4268(2001)18:1<109:AGPMFT>2.0.ZU;2-F
Fonte:
ISI
Lingua:
ENG
Soggetto:
DISTANCE MATRICES; SPATIAL AUTOCORRELATION; PHYLOGENETIC ANALYSIS; QUADRATIC ASSIGNMENT; CONFIDENCE-INTERVALS; POPULATION-STRUCTURE; REGRESSION; SIMULATION; LIZARDS; TESTS;
Keywords:
autocorrelated data; comparative method; cross-species data; nonindependent observations; permutation test; phylogenetic tree;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Social & Behavioral Sciences
Citazioni:
48
Recensione:
Indirizzi per estratti:
Indirizzo: Lapointe, FJ Univ Montreal, Dept Sci Biol, CP 6128,Succursale Ctr Ville, Montreal, PQ H3C 3J7, Canada Univ Montreal CP 6128,Succursale Ctr Ville Montreal PQ Canada H3C 3J7
Citazione:
F.J. Lapointe e T. Garland, "A generalized permutation model for the analysis of cross-species data", J CLASSIF, 18(1), 2001, pp. 109-127

Abstract

Many fields of biology employ cross-species comparisons. However, because species descend with modification from common ancestors, and rates of evolution may vary among branches of an evolutionary tree, problems of nonindependence and nonidentical distributions may occur in comparative data sets. Several phylogenetically based statistical methods have been developed to deal with these issues, but two are most commonly used. Independent contrastsattempts to transform the data to meet the i.i.d, assumption of conventional statistical methods. Monte Carlo computer simulations attempt to producephylogenetically informed null distributions of test statistics. A disadvantage of the former is its ultimate reliance on conventional distributionalassumptions, whereas the latter may require excessive information on biological parameters that are rarely known. We propose a phylogenetic permutation method that is akin to the simulation approach but requires less biological input information. We show that the conventional, equally likely (EL) randomization model is a special case of our phylogenetic permutations (PP). An application of the method is presented to test the correlation between two traits with cross-species data.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 25/11/20 alle ore 18:54:52