Secondary Analysis of PGC Data: Examples And Inspiration

Abstract

BackgroundThe PGC DAC enables PGC members to access a rich resource of clinical phenotype and genotype data which can be used to test hypotheses, explore genetic etiologies across disorders and test new statistical methods. This Education Day session will highlight some of the exciting science that the PGC members and collaborators have achieved through DAC-facilitated data. MethodsThe session will walk through specific secondary analysis proposals submitted through the DAC, showing how access to data enables a wide array of interesting hypotheses to be tested. The PGC data consists of quality controlled and harmonised genotype and phenotype data, allowing researchers to focus on their specific scientific hypothesis, avoiding weeks of data processing or multiple external data access requests. Researchers can immediately perform their own research study, making projects particularly time-effective for PhD students and postdoctoral fellows. ResultsWe will highlight proposals that1. Use summary statistics to create polygenic risk scores2. Integrate phenotype data to dissect disorder subtypes3. Bring in external data to assess, for example, physical-mental co-morbidity4. Perform cross-disorder analysis to identify genetic underpinnings that transcend current diagnostic boundaries5. Use the large sample size to test novel statistical methods, developing analytical strategies that are relevant for any disorder. ConclusionsThe aim of this session is to inform PGC members and their collaborators of the rich resource of PGC data available, and inspire them to submit Secondary Analysis Proposals to explore their own hypotheses.