PPT-Genome-Wide Association Study (GWAS)

Presented by Karen Xu What you need to know Basic genetic concepts behind GWAS Genotyping technologies and common study designs Statistical concepts for GWAS analysis Replication interpretation and followup of association results. Simonis Standard Cloth Cutting Guide for best yield use 66 wide cloth for 7 and 8 Std tables All rail cuts are 6 width No rails off the ends A u t h e n t i c A c c u r a t e A l w a y s Iwan Simonis Inc wwwsimonisclothcom 1514 St Paul Avenue Gurne HapMap. Peter Castaldi. January 29, 2013. Objectives. Introduce the concept of linkage disequilibrium (LD). Describe how the . HapMap. project provides publically available information on genetic variation and LD structure. Andrew Morris. Advanced Topics in GWAS. Toronto, 30 May 2012. Introduction. GWAS have been successful in detecting . novel loci for complex traits:. typically characterised by common variants of modest effect;. IGSS 2015 Tutorial. Ben . Domingue. Gameplan. Overview. What are polygenic scores?. How are they used?. How are they created?. You create them.. Top hits. Homebrewed Genome-wide. PRSice. . Caveats, etc.. BIOST 2055. 04/01/2015. Human Genome and Single Nucleotide Polymorphisms (SNPs). 23 chromosome pairs. 3 billion bases. A single nucleotide change between pairs of chromosomes. E.g. . Haplotype1. : AAGG. Matt . Hudson . Crop Sciences. NCSA. . HPCBio. IGB. University . of Illinois. Outline. How do we predict molecular or genetic functions using variants?. Predicting . when a coding SNP or SNV is “damaging”. for Colorectal . Cancer. Ulrike (. Riki. ) Peters. Fred Hutchinson Cancer Research Center. University of Washington. Overview. Significance and rationale. . Current efforts on rare and less frequent variants. Suxu Tan szt0038@auburn.edu GWAS analysis for resistance against enteric septicemia of catfish using the first - generation interspecific backcrosses Introduction - Catfish Y Catfish can survive i Bas E. Dutilh. March 4. th. 2013. Protein function. Phenotypic. . function. E.g. . apoptosis. GO: . Biological. . process. Cellular. . function. E.g. . ribosome. GO: . Cellular. component. Molecular. Hardy-Weinberg equilibrium. Meta-analysis. SNP Imputation. Review what we have learned about the genetics of common disease from GWAS. Where do we go from here? What do we go with GWAS results.. functional characterization of GWAS loci. Genomics Lesson 12_1. Ross . Hardison. 4/19/15. 1. Genetic association. The occurrence together in a population, more often than can be readily explained by chance, of two or more traits of which at least one is known to be genetic.. Inês Barroso. Joint Head of Human Genetics. Metabolic Disease Group Leader. Wellcome. Trust Sanger Institute. 1. Objectives. Why perform meta-analysis?. How? . What are the issues to consider?. What can you gain?. Q2. Is there such a thing as addictive personality? . Q3. What does SNP stand for? . Q4. In terms of identifying addiction risk genes, have we had any success? . . Do drugs “hijack the brain” robbing the user of their free will? . 2023 Statistical Genetics workshop . Presenter: Daniel Howrigan. Data group leader . –. Neale Lab (MGH, Broad Institute). Slides adapted from previous workshop presenters:. Lucia . Colodro. Conde (QIMR), Katrina .