A 2-step penalized regression method for family-based next-generation sequencing association studies
نویسندگان
چکیده
منابع مشابه
A 2-step penalized regression method for family-based next-generation sequencing association studies
Large-scale genetic studies are often composed of related participants, and utilizing familial relationships can be cumbersome and computationally challenging. We present an approach to efficiently handle sequencing data from complex pedigrees that incorporates information from rare variants as well as common variants. Our method employs a 2-step procedure that sequentially regresses out correl...
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Recently genetic studies have been revolutionized by next generation sequencing (NGS) technology, and it is expected that the use of this technology will largely eliminate defects in the methods of association studies. The NGS technology is becoming the premier tool in genetics. However, at the moment the use of this method is limited especially in the livestock due to high cost and computation...
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Introduction: The precision and time required for analysis of data in next-generation sequencing (NGS) depends on many factors including the tools utilized for alignment, variant calling, annotation and filtering of variants, personnel expertise in data analysis and interpretation, and computational capacity of the lab and its optimization is a challenging task. Method: An application software...
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Introduction: The precision and time required for analysis of data in next-generation sequencing (NGS) depends on many factors including the tools utilized for alignment, variant calling, annotation and filtering of variants, personnel expertise in data analysis and interpretation, and computational capacity of the lab and its optimization is a challenging task. Method: An application software...
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Penalized regression incorporating prior dependency structure of predictors can be effective in high-dimensional data analysis (Li and Li 2008). Pan, Xie and Shen (2010) proposed a penalized regression method for better outcome prediction and variable selection by smoothing parameters over a given predictor network, which can be applied to analysis of microarray data with a given gene network. ...
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ژورنال
عنوان ژورنال: BMC Proceedings
سال: 2014
ISSN: 1753-6561
DOI: 10.1186/1753-6561-8-s1-s25