Computational Methods for Genetics of Complex Traits

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Daniel Gianola - "Prediction of Complex Traits with Kernel Methods

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Complex Traits

You can go to cart and save for later there. It includes experiments, knowledge, and specific example data. This chapter also presents new statistical algorithms to identify rare variants in pedigree settings for both qualitative and quantitative traits. Chapter 4 briefly reviews the methods used to combine functional genomic data to detect complex diseases.

Chapter 4 examines the progress of research on a specific rare disorder, nasopharyngeal carcinoma NPC. Jorgensen et al. This section also emphasizes the need for an effective system to handle future community genome arrays CGAs and GWAS, to maximize their information content, and make the best use of the limited number of available NPC study populations.

Chapter 5 introduces genetic mapping of quantitative trait loci QTL , offering an efficient and powerful method to find putative regulatory regions and to discover novel functional impact of genetic variants. Here, the authors describe recent studies on QTL mapping of complex traits, including DNA methylation, gene expression, and protein expression as well as metabolites.

UC Berkeley

The authors summarize several exciting findings from eQTL analysis in various human post-mortem brain tissues based on publications, which appeared between and Chapter 6 explains the pivotal role of genetic haplotypes in gene prediction. The authors define a haplotype with the theoretical background of haplotype analysis and provide their perspective on the development of a new likelihood-based method that make predictive models using genotypes data derived from unrelated individuals.

Donghyung Lee, Ph.D.

Finally, it provides current technologies and software for a clear genetic interpretation focused on the HLA region. Chapter 7 discusses the overall knowledge on whole exome sequencing. The authors comment on current analytical challenges such as image processing, base-calling, and short read mapping, and introduce the main statistical approaches that can be used to discover rate variant and copy number variations.

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Through this chapter, the readers could grasp analytical concepts of biological big data analysis related to sequencing alignment and variant calling as well as data management. Chapter 8 introduces the strategies and mathematical algorithms for analyzing rare variants such as weighted sum association method WSM , sequence kernel association test SKAT , and odds ratio weighted sum statistic ORWSS.

Frontiers | A survey about methods dedicated to epistasis detection | Genetics

Chapter 9 introduces gene duplication and functional consequences, and focuses on copy number variation as well as segmental duplications and gene essentiality in duplicated genes, transcriptional, epigenetic divergence following gene duplication, and environmental adaptation. In this chapter, the authors use their own experimental material as an example and explain how to interpret the correlation between copy number variations and complex traits in humans, such as psychiatric disorders.

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Analysis and computational method development towards unravelling and better understanding genetic variation underlying cardiovascular and haematological complex traits Oct 19, Principal Investigator: Dr Valentina Iotchkova Institution: University of Oxford Tags: , cardiovascular , causality , genetics , Haematological , methods , regulatory Summary: The wealth of data and expertise for evaluating the genetic contribution to human traits in health and disease is continuously growing.

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