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Epistasis Analysis01:09

Epistasis Analysis

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Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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Polygenic Traits

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When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
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Genome-wide Association Studies-GWAS01:11

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Expression QTLs Mapping and Analysis: A Bayesian Perspective.

Martha Imprialou1, Enrico Petretto2, Leonardo Bottolo3,4

  • 1Centre for Complement and Inflammation Research, Imperial College London, Hammersmith Hospital, Du Cane Road, London, W12 0NN, UK.

Methods in Molecular Biology (Clifton, N.J.)
|December 10, 2016
PubMed
Summary
This summary is machine-generated.

Bayesian methods enhance expression Quantitative Trait Locus (eQTL) mapping by improving the detection of genetic variants influencing gene expression. This approach offers advantages over traditional methods for complex traits and disease research.

Keywords:
Bayesian variable selectionIT-tools for systems geneticsLASSOPenalized-regressionPolygenic eQTLtrans-eQTLs

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Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genomics

Background:

  • Expression Quantitative Trait Locus (eQTL) mapping identifies DNA variants affecting gene expression.
  • Genome-wide association studies (GWAS) have identified numerous trait-associated variants, increasing the need for functional context.
  • Current univariate eQTL methods struggle with linkage disequilibrium and detecting complex regulatory effects.

Purpose of the Study:

  • To review recent advances in eQTL mapping, focusing on Bayesian methodologies.
  • To highlight the advantages of Bayesian approaches over frequentist methods in eQTL analysis.
  • To discuss the benefits of multivariate eQTL mapping for complex trait genetics.

Main Methods:

  • Review of Bayesian methodology for eQTL mapping.
  • Empirical example comparing frequentist and Bayesian approaches for polygenic eQTL analysis.
  • Discussion of multivariate eQTL mapping strategies.

Main Results:

  • Bayesian methods offer improved control of false positives in complex linkage disequilibrium structures.
  • Bayesian approaches provide greater power to detect trans-acting regulatory effects.
  • Multivariate eQTL mapping enhances the detection and interpretability of polygenic effects.

Conclusions:

  • Bayesian methodology represents a significant advancement for eQTL mapping, particularly for complex genetic architectures.
  • Multivariate approaches are crucial for accurately characterizing polygenic regulatory effects.
  • These advanced eQTL mapping strategies are vital for understanding the functional basis of complex traits and diseases.