In recent years, the amount of publicly available summary data from genome-wide association studies (GWAS) has rapidly increased. So too has the number of researchers accessing and utilizing these data. These summary data can be used in many subsequent analyses, including Mendelian randomization, genetic correlation and polygenic score analysis. It is therefore vital that we can ensure consistency across these datasets to minimize the risk of analytical mistakes due to user error. One such inconsistency is the naming of the effect allele in these datasets. This is of particular concern given the increasing availability of automated software packages for downstream analyses (e.g. MR-Base, 1 LDpred, 2 LD Hub 3)...
- Physical and Mental Health
- Mental Health Data Science