CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies
نویسندگان
چکیده
منابع مشابه
Predictive rule inference for epistatic interaction detection in genome-wide association studies
MOTIVATION Under the current era of genome-wide association study (GWAS), finding epistatic interactions in the large volume of SNP data is a challenging and unsolved issue. Few of previous studies could handle genome-wide data due to the difficulties in searching the combinatorially explosive search space and statistically evaluating high-order epistatic interactions given the limited number o...
متن کاملSNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies
MOTIVATION Hundreds of thousands of single nucleotide polymorphisms (SNPs) are available for genome-wide association (GWA) studies nowadays. The epistatic interactions of SNPs are believed to be very important in determining individual susceptibility to complex diseases. However, existing methods for SNP interaction discovery either suffer from high computation complexity or perform poorly when...
متن کاملFamily-based genome-wide association studies.
In the last 2 years, the effort to identify genes affecting common diseases and complex traits has been accelerated through the use of genome-wide association studies (GWAS). The availability of existing large collections of linkage data paved the way for the use of family-based GWAS. Although most published GWAS used population-based designs, family-based designs have played an important role,...
متن کاملGenome-wide Association Studies
Progress in probabilistic generative models has accelerated, developing richer models with neural architectures, implicit densities, and with scalable algorithms for their Bayesian inference. However, there has been limited progress in models that capture causal relationships, for example, how individual genetic factors cause major human diseases. In this work, we focus on two challenges in par...
متن کاملGenome-wide Association Studies
Progress in probabilistic generative models has accelerated, developing richer models with neural architectures, implicit densities, and with scalable algorithms for their Bayesian inference. However, there has been limited progress in models that capture causal relationships, for example, how individual genetic factors cause major human diseases. In this work, we focus on two challenges in par...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2017
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/btx163