The objective of this project is to develop software for the analysis of data from large-scale genotyping and sequencing studies, building on the existing software package PLINK and its companion package PLINK/Seq. Designed to manipulate and analyze whole-genome SNP datasets, PLINK has been actively developed for over six years and has a wide base of users, with over 5000 citations in peer-reviewed journals. Over the past years, we have added considerable support for the analysis of large rare variant datasets, primarily focused on whole-exome sequencing studies in PLINK/Seq. In this renewal application, we seek to 1) provide tighter integration between PLINK and PLINK/Seq, aiming to provide a single interface for both genome-wide association and sequencing studies, particularly in the context of large statistically-imputed datasets;2) enhance the data-integration facilities already present, across different classes of genetic variation as well as large, diverse datasets;3) provide improved handling of family-based datasets, focused on de novo and inherited variation in (nuclear) family-based association studies;4) to work on improving performance on very large datasets. Particular attention will be paid to ensure interoperability with other major software, file-formats and resources that are generated by the broader genetics community.
This Project is to develop software for the analysis of large datasets from modern genetic studies. New high-throughput genotyping and sequencing technologies are capable of producing vast amounts of data, but there is a need for analytic tools that biomedical researchers can use. These studies have the potential to uncover genetic determinants for a large number of diseases and traits, which can be relevant for prediction of risk, and give insight into novel targets for treatments.
|Fromer, Menachem; Purcell, Shaun M (2014) Using XHMM Software to Detect Copy Number Variation in Whole-Exome Sequencing Data. Curr Protoc Hum Genet 81:7.23.1-7.23.21|
|Sham, Pak C; Purcell, Shaun M (2014) Statistical power and significance testing in large-scale genetic studies. Nat Rev Genet 15:335-46|
|Purcell, Shaun M; Moran, Jennifer L; Fromer, Menachem et al. (2014) A polygenic burden of rare disruptive mutations in schizophrenia. Nature 506:185-90|
|Fromer, Menachem; Pocklington, Andrew J; Kavanagh, David H et al. (2014) De novo mutations in schizophrenia implicate synaptic networks. Nature 506:179-84|