[PDF] Top 20 Genome wide association analysis of GAW17 data using an empirical Bayes variable selection
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Genome wide association analysis of GAW17 data using an empirical Bayes variable selection
... With the advent of next-generation sequencing, rare variants such as single-nucleotide polymorphisms (SNPs) with a minor allele frequency (MAF) less than 5% are getting more attention in genome-wide ... See full document
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Application of an iterative Bayesian variable selection method in a genome wide association study of rheumatoid arthritis
... another data set in which each case-control panel again consists of ten cases and controls (five each) randomly selected from each of case-control panels in DS1, but the 50 SNPs were selected in a wide ... See full document
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Combining least absolute shrinkage and selection operator (LASSO) and principal components analysis for detection of gene gene interactions in genome wide association studies
... marker data and detect gene-gene interaction signals on chromosome ...ing variable selection and dimension-reduction techni- ...the data to detect signals from variants and gene-gene ... See full document
5
r2VIM: A new variable selection method for random forests in genome wide association studies
... novel variable selection procedure called recurrent relative variable importance measure ...GWAS data with realistic local linkage disequilibrium patterns were simulated to evaluate ... See full document
15
Causal graph-based analysis of genome-wide association data in rheumatoid arthritis
... TIE* using GLL (Generalized Local Learning) as the base Markov boundary induction algorithm ...its empirical performance in biomedical high- throughput data and its theoretical properties ...by ... See full document
13
Analysis of genome wide association data by large scale Bayesian logistic regression
... prior using BBRBMR software on the training ...results using these two selection ...SNPs using the independent testing sample. We analyzed data under both a dominant and additive ... See full document
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Selection of important variables by statistical learning in genome wide association analysis
... BNT is a graphical model used to learn structure (joint multivariate probability distribution) of a set of random variables that reflects relationships of dependence and conditional independence among them [8,9]. In a ... See full document
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Exploration of empirical Bayes hierarchical modeling for the analysis of genome wide association study data
... window using HapMap CEU ...(2005)), using a variety of databases, was integrated with SNAP, and together with custom PERL scripts, was used to facilitate these functional an- notations of the ... See full document
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Structured Genome-Wide Association Studies with Bayesian Hierarchical Variable Selection
... GWAS analysis on imaging phenotypes related to AD, and our goal is to identify genetic markers that are associated with imaging traits, and to further assess their predictive ...of using imaging phenotypes ... See full document
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Comparison between the stochastic search variable selection and the least absolute shrinkage and selection operator for genome wide association studies of rheumatoid arthritis
... Genetic Analysis Workshop 16 data includes 2,062 unrelated individuals and 545,080 single-nucleotide polymorphism markers from the Illumina 550 k ...phenotype data was not provided for the ... See full document
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Genetic Control of Canine Leishmaniasis: Genome-Wide Association Study and Genomic Selection Analysis
... lifestyle. Using PLINK [48], an identical-by-state correlation matrix for n individuals was calculated from which n dimensions were extracted using MDS analysis, resulting in a matrix of n- samples ... See full document
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Genome wide association analysis of the QTL MAS 2012 data investigating pleiotropy
... genomic selection when negatively correlated traits are ...the analysis of PCs were generally more powerful and accurate than the single trait analysis ... See full document
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A "Candidate Interactome" Aggregate Analysis of Genome Wide Association Data in Multiple Sclerosis
... set analysis are in their early stage of development and there are still potential sources of bias or discrepancy among different methods, including those used in our ...Pathway Analysis of each ...the ... See full document
9
A "candidate interactome" aggregate analysis of genome wide association data in multiple sclerosis
... of association for each tested SNP were obtained from the International Multiple Sclerosis Genetics Consortium & Wellcome Trust Case Control Consortium,2 ...an empirical approach, comparing each ... See full document
9
Software Application Profile:mrrobust A Tool For Performing Two Sample Summary Mendelian Randomization Analyses
... instrument-outcome association estimate for each variant is illustrated using vertical error bars, whilst horizontal error bars pertaining to the instrument-exposure association may be omitted for ... See full document
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The discovery BPD (D-BPD) program: study protocol of a prospective translational multicenter collaborative study to investigate determinants of chronic lung disease in very low birth weight infants
... of data that will be amassed during the present study and the urgent need for more stringent dissection of the causes and outcomes under the BPD diagnosis supports the use of machine learning [25] for assessing ... See full document
10
Genome wide association analysis of rheumatoid arthritis data via haplotype sharing
... excluded data from SNPs that had extensive missingness (missingness >10), devia- tions from Hardy-Weinberg equilibrium (p-value < ...remained. Using the software package PLINK [7], we confirmed that ... See full document
5
Genome wide analysis of DNA methylation patterns
... array-based analysis of DNA methylation developed by Illumina is an outgrowth of their genotyping method (Bibikova et ...ascertained using Illumina’s Sentrix Array Matrix bead array platform, which can ... See full document
7
Mendelian randomization provides support for obesity as a risk factor for meningioma.
... estimates in previous observational epidemiological studies. MR-Egger analysis of each obesity- related trait did not identify bias caused by directional pleiotropy (see Supplementary Table S3 online). Therefore, ... See full document
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A LASSO penalized regression approach for genome wide association analyses using related individuals: application to the Genetic Analysis Workshop 19 simulated data
... particular data, it appears that using the more complex modeling of the covariance structure of the random effect had no significant effect on the performance of the method, as the results from both the ... See full document
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