Published PGC results can be viewed using ”ricopili” , a web site that generates high-resolution images of PGC results. This web resource takes as input a gene name or genomic region, and produces a plot of PGC findings in genomic context. Thanks to Stephan Ripke and Brett Thomas of the Broad Institute.
Example output from ricopili, MHC region in schizophrenia and CACNA1C in bipolar disorder.
There are several options for obtaining results.
- PGC members can obtain full results for any disease to which they contributed data (contact the working group chair for more information).
- Individual-level genotype and phenotype data requires application, material transfer agreement, and informed consent consideration. PGC analytic datasets can be obtained by application to the controlled-access NIMH Genetics Repository. Some datasets are also in the controlled-access dbGaP and Wellcome Trust Case-Control Consortium repositories. These data can be obtained by any credible investigator.
- NHGRI GWAS Catalog. This catalog contains updated information about all GWAS in biomedicine, and is usually an excellent starting point to find a comprehensive list of studies.
- The PGC has made the full results from all published PGC studies available for download. Click here to go to the downloads page.
The PGC is committed to full and open sharing of data and results since its inception. This has become the community standard in human genetics, and is mandated by one of our funders (the US National Institutes of Mental Health). However, data sharing occasionally cannot be done due to national laws or because of ethical review or informed consent restrictions.
PGC investigators ascribe to a scientific approach akin to “open-source” approaches to the development of computer code. The key advantage of open-source is the speed of progress. The extension to the genetics of psychiatric disorders is clear: the more qualified research groups that can work on the genetics of these important human conditions, the more likely we are to see tangible and verifiable progress. The main goal is to maximize our knowledge and an “open-source” approach is consistent with this aim.
Most major funders in the EU and the US consider the sharing of unique research resources developed through sponsored research an important means to enhance the value and further the advancement of the research. It is important that they be made readily available for research purposes to qualified individuals within the scientific community. The data sharing plan of the PGC adheres to community standards in human genetics, as well as with EU and NIH guidelines (NOT-OD-08-013). All data sharing must conform to local IRB approval, individual written informed consents, and national law.
All individual level genetic data plus relevant phenotypes generated and used for funded analyses in the PGC, along with documentation sufficient for interpretation of data (e.g., study protocol and manuals, data collection instruments) have been made available via in an NIMH-approved controlled-access repository (NIMH repository). Many are also available in dbGaP.
All members of the PGC have formally indicated their agreement with the PGC Memorandum of Understanding with contains the following paragraph:
We encourage a responsible approach to management of intellectual property derived from downstream discoveries that is consistent with the recommendations of the NIH's Best Practices for the Licensing of Genomic Inventions and and the NIH Research Tools Policy. The management of patent applications in a manner that might restrict use of the joint findings and that could substantially diminish the value and public benefit provided by these resources is discouraged.
We have a shared commitment to protect the confidentiality of data and to protect PGC analyses ensuring that no use of the data can be published in advance of an agreed-upon group publication and/or data release. At the same time we also recognize that each participating group (either individually or as consortia) are actively pursuing follow-up genetic and functional work.
Thus, individual parties performing additional experiments on genes identified or replicated in exchanges of data are not in violation of this agreement. However, we reaffirm that results of downstream experiments of genes identified in the meta-analysis cannot be published in advance of meta-analysis release or publication. We affirm a desire that purely genetic confirmation experiments (i.e., typing in additional replication samples) be done as a component of PGC collaborations.