MINED: An Efficient Mutual Information Based Epistasis Detection Method to Improve Quantitative Genetic Trait Prediction
نویسندگان
چکیده
1:00pm-5:00pm Mini-tutorials TBD Software tools for NGS data analysis Yvette Blanche Temate-Tiagueu and Alex Zelikovsky Computational methods for advanced molecular detection and surveillance of viral transmissions and outbreaks David S. Campo and Pavel Skums Computational methods for genomics-guided immunotherapy Sahar Al Seesi and Ion Mandoiu
منابع مشابه
MUSE: A Multi-locus Sampling-based Epistasis Algorithm for Quantitative Genetic Trait Prediction
Quantitative genetic trait prediction based on high-density genotyping arrays plays an important role for plant and animal breeding, as well as genetic epidemiology such as complex diseases. The prediction can be very helpful to develop breeding strategies and is crucial to translate the findings in genetics to precision medicine. Epistasis, the phenomena where the SNPs interact with each other...
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Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the featur...
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