We need to create a meta QC report that summarises and compares all QC metrics across all studies. This will be the most effective way for spotting outliers and problematic studies. For example, the report will create scatter plots for each QC metric plotted against sample size across studies. The studies should be organised according to their phenotype relatedness or ontology (because comparisons will be most valid when comparing traits with similar genetic architectures). This will require cluster analysis of the traits based on correlation matrices, using either genetic or observational data. Ben has generated some correlations that could be used for this. Alternatively the traits need to be mapped to an ontology.
We need to create a meta QC report that summarises and compares all QC metrics across all studies. This will be the most effective way for spotting outliers and problematic studies. For example, the report will create scatter plots for each QC metric plotted against sample size across studies. The studies should be organised according to their phenotype relatedness or ontology (because comparisons will be most valid when comparing traits with similar genetic architectures). This will require cluster analysis of the traits based on correlation matrices, using either genetic or observational data. Ben has generated some correlations that could be used for this. Alternatively the traits need to be mapped to an ontology.