1. A tutorial on conducting genome-wide association studies: Quality control and statistical analysis
- Author
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Eske M. Derks, Andries T. Marees, Hilde de Kluiver, Cynthia Marie-Claire, Florence Vorspan, Sven Stringer, Emmanuel Curis, Optimisation Thérapeutique en Neuropsychopharmacologie (VariaPsy - U1144), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Diderot - Paris 7 (UPD7), Université Paris Descartes - Paris 5 (UPD5), Université Paris Diderot - Paris 7 (UPD7), Université Sorbonne Paris Cité (USPC), Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (APHP), Université Paris Descartes - Faculté de Pharmacie de Paris (UPD5 Pharmacie), Service de biostatistique et information médicale de l’hôpital Saint Louis (Equipe ECSTRA) (SBIM), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut national du cancer [Boulogne] (INCA)-CHU Saint Louis [APHP], QIMR Berghofer Medical Research Institute, Variabilité de réponse aux Psychotropes (VariaPsy - U1144), Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Hopital Saint-Louis [AP-HP] (AP-HP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut national du cancer [Boulogne] (INCA)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), APH - Mental Health, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Graduate School, Adult Psychiatry, ANS - Complex Trait Genetics, Complex Trait Genetics, and Biological Psychology
- Subjects
0301 basic medicine ,Quality Control ,Multifactorial Inheritance ,Computer science ,polygenic risk score (PRS) ,media_common.quotation_subject ,Control (management) ,Genome-wide association study ,Guidelines as Topic ,computer.software_genre ,Polymorphism, Single Nucleotide ,Risk Assessment ,Field (computer science) ,GitHub ,03 medical and health sciences ,tutorial ,Software ,[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,Humans ,PLINK ,Statistical analysis ,Quality (business) ,ComputingMilieux_MISCELLANEOUS ,Genetic association ,media_common ,business.industry ,genome-wide association study (GWAS) ,Data science ,Psychiatry and Mental health ,030104 developmental biology ,Scripting language ,Data Interpretation, Statistical ,business ,computer ,Genome-Wide Association Study - Abstract
Objectives: Genome-wide association studies (GWAS) have become increasingly popular to identify associations between single nucleotide polymorphisms (SNPs) and phenotypic traits. The GWAS method is commonly applied within the social sciences. However, statistical analyses will need to be carefully conducted and the use of dedicated genetics software will be required. This tutorial aims to provide a guideline for conducting genetic analyses. Methods: We discuss and explain key concepts and illustrate how to conduct GWAS using example scripts provided through GitHub (https://github.com/MareesAT/GWA_tutorial/). In addition to the illustration of standard GWAS, we will also show how to apply polygenic risk score (PRS) analysis. PRS does not aim to identify individual SNPs but aggregates information from SNPs across the genome in order to provide individual-level scores of genetic risk. Results: The simulated data and scripts that will be illustrated in the current tutorial provide hands-on practice with genetic analyses. The scripts are based on PLINK, PRSice, and R, which are commonly used, freely available software tools that are accessible for novice users. Conclusions: By providing theoretical background and hands-on experience, we aim to make GWAS more accessible to researchers without formal training in the field.
- Published
- 2018