A tutorial on conducting genome‐wide association studies: Quality control and statistical analysis

By A. Marees, H. de Kluiver, S. Stringer, F. Vorspan, Emmanuel Curis, Cynthia Marie-Claire, Eske M. Derks. International Journal of Methods in Psychiatric Research, 2018

684 citations recorded by the source corpus.

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.

Subfields: General Social Sciences

View Paper: https://www.semanticscholar.org/paper/3dd2fb1b4a271c2914db4d7b3f77c85bef911034

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Citations in the corpus

• MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation (2024, methodology): “The next step is to perform SNP filtering and harmonization to identify independent SNPs through linkage disequilibrium (LD) clumping ( 34 ).”
• Empowering Biomedical Discovery with AI Agents (2024, neutral): “…control measures, such as the removal of single-nucleotide polymorphisms (SNPs) missing in many individuals or control for population stratification [88], (2) estimate ungenotyped SNPs through imputation, and (3) conduct the appropriate statistical analyses to identify relevant SNPs, taking into…”