Examinando por Autor "Eyheramendy, Susana"
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Ítem A machine learned classifier for RR Lyrae in the VVV survey(EDP Sciences, 2016-11) Elorrieta, Felipe; Eyheramendy, Susana; Jordán, Andrés; Dékány, István; Catelan, Márcio; Angeloni, Rodolfo; Alonso-García, Javier; Contreras-Ramos, Rodrigo; Gran, Felipe; Hajdu, Gergely; Espinoza, Néstor; Saito, Roberto K.; Minniti, DanteVariable stars of RR Lyrae type are a prime tool with which to obtain distances to old stellar populations in the Milky Way. One of the main aims of the Vista Variables in the Via Lactea (VVV) near-infrared survey is to use them to map the structure of the Galactic Bulge. Owing to the large number of expected sources, this requires an automated mechanism for selecting RR Lyrae, and particularly those of the more easily recognized type ab (i.e., fundamental-mode pulsators), from the 106−107 variables expected in the VVV survey area. In this work we describe a supervised machine-learned classifier constructed for assigning a score to a Ks-band VVV light curve that indicates its likelihood of being ab-type RR Lyrae. We describe the key steps in the construction of the classifier, which were the choice of features, training set, selection of aperture, and family of classifiers. We find that the AdaBoost family of classifiers give consistently the best performance for our problem, and obtain a classifier based on the AdaBoost algorithm that achieves a harmonic mean between false positives and false negatives of ≈7% for typical VVV light-curve sets. This performance is estimated using cross-validation and through the comparison to two independent datasets that were classified by human experts.Ítem Whole Genome Sequence, Variant Discovery and Annotation in Mapuche-Huilliche Native South Americans(Nature Publishing Group, 2019-12) Vidal, Elena A.; Moyano, Tomás C.; Bustos, Bernabé I.; Pérez-Palma, Eduardo; Moraga, Carol; Riveras, Eleodoro; Montecinos, Alejandro; Azócar, Lorena; Soto, Daniela C.; Vidal, Mabel; Genova, Alex Di; Puschel, Klaus; Nürnberg, Peter; Buch, Stephan; Hampe, Jochen; Allende, Miguel L.; Cambiazo, Verónica; González, Mauricio; Hodar, , Christian; Montecino, Martín; Muñoz-Espinoza, Claudia; Orellana, Ariel; Reyes-Jara, Angélica; Travisany, Dante; Vizoso, Paula; Moraga, Mauricio; Eyheramendy, Susana; Maass, Alejandro; Ferrari, Giancarlo V. De; Miquel, Juan Francisco; Gutiérrez, Rodrigo A.Whole human genome sequencing initiatives help us understand population history and the basis of genetic diseases. Current data mostly focuses on Old World populations, and the information of the genomic structure of Native Americans, especially those from the Southern Cone is scant. Here we present annotation and variant discovery from high-quality complete genome sequences of a cohort of 11 Mapuche-Huilliche individuals (HUI) from Southern Chile. We found approximately 3.1 × 10 6 single nucleotide variants (SNVs) per individual and identified 403,383 (6.9%) of novel SNVs events. Analyses of large-scale genomic events detected 680 copy number variants (CNVs) and 4,514 structural variants (SVs), including 398 and 1,910 novel events, respectively. Global ancestry composition of HUI genomes revealed that the cohort represents a sample from a marginally admixed population from the Southern Cone, whose main genetic component derives from Native American ancestors. Additionally, we found that HUI genomes contain variants in genes associated with 5 of the 6 leading causes of noncommunicable diseases in Chile, which may have an impact on the risk of prevalent diseases in Chilean and Amerindian populations. Our data represents a useful resource that can contribute to population-based studies and for the design of early diagnostics or prevention tools for Native and admixed Latin American populations. © 2019, The Author(s).