Titlebook: eQTL Analysis; Methods and Protocol Xinghua Mindy Shi Book 2020 Springer Science+Business Media, LLC, part of Springer Nature 2020 mining.g

EWER

Identification and Quantification of Splicing Quantitative Trait Locimains one of the most important objectives of current biomedical research. Unlike Mendelian or familial diseases, which are usually caused by mutations in the coding regions of individual genes, complex diseases are thought to result from the cumulative effects of a large number of variants, of whic

affect

ADORE

Combining eQTL and SNP Annotation Data to Identify Functional Noncoding SNPs in GWAS Trait-Associatedetected as trait-associated in a population-based genome-wide association study (GWAS). Our method’s key step is to combine, within a naïve Bayes-like framework, three quantities for each SNP: (1) the .-value for the association test between the SNP’s genotype and the trait; (2) the .-value for the

BROTH

Statistical and Machine Learning Methods for eQTL Analysiscing capabilities and better genotyping methods, we are now able to more fully appreciate how regulation of gene expression is consequential to one’s genotypes in coding and non-coding DNA. The identification of genetic loci that contribute to quantifiable variation in genetic expression is critical

ordain

Sparse Regression Models for Unraveling Group and Individual Associations in eQTL Mappingarch interest. Traditional eQTL methods focus on testing the associations between individual single-nucleotide polymorphisms (SNPs) and gene expression traits. A major drawback of this approach is that it cannot model the joint effect of a set of SNPs on a set of genes, which may correspond to biolo

FID

Exploring Bayesian Approaches to eQTL Mapping Through Probabilistic Programming regression problem. An important aspect in the development of such models is the implementation of bespoke inference methodologies, a process which can become quite laborious, when multiple candidate models are being considered. We describe automatic, black-box inference in such models using ., a p

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玉米

山崩

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Expression Quantitative Trait Loci (eQTL) Analysis in Cancerumor samples can provide an intermediate phenotype between genetic variation and complex traits to better understand how risk alleles contribute to tumorigenesis and development. Here we describe a detailed workflow for identifying eQTLs in cancer using existing packages and software. The key packag