BALZARINI MONICA GRACIELA
Artículos
Título:
Assessing spatial genetic structure from molecular marker data via principal component analyses: A case study in a Prosopis sp. forest
Autor/es:
INGRID TEICH; ANIBAL VERGA; MÓNICA BALZARINI
Revista:
Advances in Bioscience and Biotechnology
Editorial:
Scientific Research Publishing
Referencias:
Año: 2014 vol. 5 p. 89 - 89
ISSN:
2156-8456
Resumen:
dvances in genotyping technology, such as molecular markers, have noticeably improved our capacity to characterize genomes at multiple loci. Concomitantly, the methodological framework to analyze genetic data has expanded, and keeping abreast with the latest statistical developments to analyze molecular marker data in the context of spatial genetics has become a difficult task. Most methods in spatial statistics are devoted to univariate data whereas the nature of molecular marker data is highly dimensional. Multivariate methods are aimed at finding proximities between entities characterized by multiple variables by summarizing information in few synthetic variables. In particular, Principal Compo-nent analysis (PCA) has been used to study genetic structure of geo-referenced allele frequency profiles, incorporating spatial information a posteriori of the analysis. Conversely, the recently developed spatially restricted PCA (sPCA) explicitly includes spatial data in the optimization cr