Difference between revisions of "Metabolomics— Linking Genotype and Phenotype"
| Line 1: | Line 1: | ||
| − | '''Background''': It has been well established that genetic variants strongly affect | + | '''Background''': It has been well established that genetic variants strongly affect diseases and other heritable traits. In a basic Genome-Wide Association Study (GWAS), individuals are genotyped with a dense SNP array to identify their genotypes across common genetic variations. Eventually GWAS aims to explore these genetic variations that can have a role in diseases or quantitative traits that are risk factors for the diseases. |
'''Goal''': Students will learn the key concepts of the design and analysis of GWAS for common diseases and complex traits. With the help of statistical tools they will observe the links between Genotype - Metabotype - Phenotype and relate their findings with the published research. | '''Goal''': Students will learn the key concepts of the design and analysis of GWAS for common diseases and complex traits. With the help of statistical tools they will observe the links between Genotype - Metabotype - Phenotype and relate their findings with the published research. | ||
| − | '''Mathematical tools''': Students will use Matlab to do the association analysis with main emphasis on linear regression. Various visual data representation techniques like correlation plots, qq-plots and | + | '''Mathematical tools''': Students will use Matlab to do the association analysis with main emphasis on linear regression. Various visual data representation techniques like correlation plots, qq-plots and Manhattan plots will also be studied. |
'''Biological or Medical aspects''': The students will get insight of this new groundbreaking discipline to explore the relationship between sequence variations and disease susceptibility. | '''Biological or Medical aspects''': The students will get insight of this new groundbreaking discipline to explore the relationship between sequence variations and disease susceptibility. | ||
'''Supervisor''': [[User:Reyhan|Reyhan Sonmez Flitman]] | '''Supervisor''': [[User:Reyhan|Reyhan Sonmez Flitman]] | ||
Revision as of 09:46, 20 February 2015
Background: It has been well established that genetic variants strongly affect diseases and other heritable traits. In a basic Genome-Wide Association Study (GWAS), individuals are genotyped with a dense SNP array to identify their genotypes across common genetic variations. Eventually GWAS aims to explore these genetic variations that can have a role in diseases or quantitative traits that are risk factors for the diseases.
Goal: Students will learn the key concepts of the design and analysis of GWAS for common diseases and complex traits. With the help of statistical tools they will observe the links between Genotype - Metabotype - Phenotype and relate their findings with the published research.
Mathematical tools: Students will use Matlab to do the association analysis with main emphasis on linear regression. Various visual data representation techniques like correlation plots, qq-plots and Manhattan plots will also be studied.
Biological or Medical aspects: The students will get insight of this new groundbreaking discipline to explore the relationship between sequence variations and disease susceptibility.
Supervisor: Reyhan Sonmez Flitman
