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1.
Hum Reprod ; 37(7): 1375-1378, 2022 06 30.
Artículo en Inglés | MEDLINE | ID: mdl-35604365

RESUMEN

Recent advances in developing polygenic scores have made it possible to screen embryos for common, complex conditions and traits. Polygenic embryo screening (PES) is currently offered commercially, and though there has been much recent media and academic coverage, reproductive specialists' points of view have not yet been prominent in these discussions. We convened a roundtable of multidisciplinary experts, including reproductive specialists to discuss PES and its implications. In this Opinion, we describe four clinically relevant issues associated with the use of PES that have not yet been discussed in the literature and warrant consideration.


Asunto(s)
Tamizaje Masivo , Herencia Multifactorial , Atención , Embrión de Mamíferos , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Humanos , Fenotipo
2.
Bioinformatics ; 21(10): 2301-8, 2005 May 15.
Artículo en Inglés | MEDLINE | ID: mdl-15722375

RESUMEN

SUMMARY: We introduce a novel unsupervised approach for the organization and visualization of multidimensional data. At the heart of the method is a presentation of the full pairwise distance matrix of the data points, viewed in pseudocolor. The ordering of points is iteratively permuted in search of a linear ordering, which can be used to study embedded shapes. Several examples indicate how the shapes of certain structures in the data (elongated, circular and compact) manifest themselves visually in our permuted distance matrix. It is important to identify the elongated objects since they are often associated with a set of hidden variables, underlying continuous variation in the data. The problem of determining an optimal linear ordering is shown to be NP-Complete, and therefore an iterative search algorithm with O(n3) step-complexity is suggested. By using sorting points into neighborhoods, i.e. SPIN to analyze colon cancer expression data we were able to address the serious problem of sample heterogeneity, which hinders identification of metastasis related genes in our data. Our methodology brings to light the continuous variation of heterogeneity--starting with homogeneous tumor samples and gradually increasing the amount of another tissue. Ordering the samples according to their degree of contamination by unrelated tissue allows the separation of genes associated with irrelevant contamination from those related to cancer progression. AVAILABILITY: Software package will be available for academic users upon request.


Asunto(s)
Algoritmos , Biomarcadores de Tumor/metabolismo , Neoplasias del Colon/metabolismo , Perfilación de la Expresión Génica/métodos , Almacenamiento y Recuperación de la Información/métodos , Proteínas de Neoplasias/metabolismo , Interfaz Usuario-Computador , Biomarcadores de Tumor/clasificación , Análisis por Conglomerados , Neoplasias del Colon/diagnóstico , Neoplasias del Colon/genética , Gráficos por Computador , Simulación por Computador , Interpretación Estadística de Datos , Diagnóstico por Computador/métodos , Humanos , Modelos Biológicos , Proteínas de Neoplasias/clasificación , Reconocimiento de Normas Patrones Automatizadas/métodos , Programas Informáticos
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