PPT-GWAS Consortia and Meta-Analysis

Inês Barroso Joint Head of Human Genetics Metabolic Disease Group Leader Wellcome Trust Sanger Institute 1 Objectives Why perform metaanalysis How What are the issues to consider What can you gain. . from. . the. ENIGMA–DTI Working Group. . Neda Jahanshad. 1#. , . Peter . Kochunov. 2#. , Emma Sprooten. 3,4. , René C. Mandl. 5. , Thomas E. Nichols. 6,7. , Laura Almasy. 8. , John Blangero. 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. EPI 811 Individual Presentation. Chapter 10 of . Szklo. and Nieto’s . Epidemiology: Beyond the Basics. Anton Frattaroli. Sensitivity Analysis. Generally, an assessment of how systematic or random errors affect an effect estimates’ representativeness of the actual effect (the validity of the effect estimate).. Imputing big data from GWAS. What we’ll be covering today.... ...we will discuss genome-wide aspects of genetic epidemiological studies focusing on meta-analyses of imputed data. . . Discuss basic theory behind GWAS, imputation and large-scale meta-analyses.. UK . Stata. users’ Group. London, 13. th. September 2013. Ian . White. MRC Biostatistics Unit, Cambridge, UK. Plan. Ordinary (. pairwise. ) meta-analysis. Multiple treatments: indirect comparisons, consistency, inconsistency. Jaswin Sawhney. Maine Medical Center. Portland, Maine. Introduction to Meta-Analysis. What is a systematic review? . A systematic review is a research methodology that tries to identify, select, appraise, and synthesize all research evidence relevant to a specific research question . 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. Introduction to Meta-Analysis. Dr. Chris L. S. . Coryn. Kristin A. Hobson. Fall 2013. Agenda. Course overview. An overview of and brief introduction to meta-analysis. Selection of working groups. In-class activity. Objective. Understand the philosophy of meta-analysis and its contribution to epidemiology and science.. Understand the limitations of meta-analysis. Introduction. Systematic quantitative integration of results . Kesheng Wang, PhD. Department of Biostatistics and Epidemiology. College of Public Health. East Tennessee State University. 2. Outline. Introduction . Alcohol dependence (AD). Genetic study. . Subjects and Methods. Outline. Introduction. Two review papers. Quality control (. MetaQC. ). Meta-analysis for detecting differentially expressed genes (. MetaDE. ). Meta-analysis for detecting pathways (. MetaPath. ). 1. Introduction. 1 - analysis Tony Hak, Henk van Rhee , & Robert Suurmond Version 1.0, March 2016 Version 1.3, Updated June 2018 Version 1 .4, Updated July 2018 Meta - analysis is a systematic method for synthesizing Sebanti Sengupta. 11/15/2017. Background. Meta-analysis an important strategy for genetic association studies. Increases sample size and power. Can lead to discovery of novel loci. Can use previously published study results. Presented by Christine R. Wells, Ph.D.. Statistical Methods and Data Analytics. UCLA Office of Advanced Research Computing. What to expect from this workshop. Definition of systematic review and meta-analysis.