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Human Genetics01:28

Human Genetics

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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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Incomplete Dominance01:43

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Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
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Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
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Single Nucleotide Polymorphisms-SNPs01:05

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Infinium Assay for Large-scale SNP Genotyping Applications
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BiU-Net: Una U-Net Biológicamente Informada para la Imputación del Genotipo

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    BiU-Net mejora la imputación del genotipo para los estudios de asociación de todo el genoma al preservar el contexto genómico. Este modelo de aprendizaje profundo informado biológicamente imputa con precisión variantes comunes y raras en diversos conjuntos de datos.

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    Área de la Ciencia:

    • La genómica
    • La bioinformática
    • Biología computacional

    Sus antecedentes:

    • Los genotipos faltantes en los datos genómicos reducen el poder estadístico para los estudios de asociación de todo el genoma (GWAS).
    • Los métodos de imputación basados en referencias se enfrentan a desafíos en regiones genómicas complejas y con desajustes de población.
    • Los modelos actuales de aprendizaje profundo sin referencia luchan con la imputación de variantes raras, especialmente en conjuntos de datos más pequeños.

    Objetivo del estudio:

    • Desarrollar un nuevo modelo de aprendizaje profundo, BiU-Net, para la imputación precisa del genotipo.
    • Mejorar la imputación de variantes raras y preservar el contexto genómico.
    • Evaluar el rendimiento de BiU-Net en comparación con los métodos de última generación existentes.

    Principales métodos:

    • BiU-Net, una arquitectura U-Net biológicamente informada, se desarrolló para segmentar los datos de genotipo.
    • El modelo codifica información posicional para mantener el contexto genómico durante la imputación.
    • El rendimiento se evaluó en tres conjuntos de datos diversos: el Proyecto 1000 Genomas, el Estudio de Osteoporosis de Luisiana y el Proyecto de Diversidad del Genoma Simons.

    Principales resultados:

    • BiU-Net demostró un rendimiento superior en comparación con el Beagle y un autoencoder de denocificación convolucional escaso.
    • El modelo logró mejores métricas de imputación generales en todos los conjuntos de datos evaluados.
    • BiU-Net mostró mejoras significativas en la imputación de variantes raras, particularmente cuando se estratifican por frecuencia de alelos menores.

    Conclusiones:

    • BiU-Net ofrece un enfoque robusto y biológicamente informado para la imputación de genotipos.
    • El modelo aborda efectivamente las limitaciones de los métodos existentes, especialmente para la imputación de variantes raras.
    • BiU-Net es prometedor para mejorar la precisión y el poder de los estudios de asociación de todo el genoma.