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Many of our seminars and public events this year will continue as in person or as hybrid (online and in person) events.

Please check our website listings and social media feeds @STICERD_LSE at X and @LSE-STICERD-CASE at Bluesky for updates.

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Unless otherwise specified, in-person seminars are open to the public. Please ensure you have informed the event contact as early as possible.

Those unable to join the seminars in-person are welcome to participate via zoom if the event is hybrid.

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About this event

Numerous statistical models have been proposed to analyze cross-trait genetic architectures utilizing summary statistics from genome-wide association studies (GWAS). However, systematically analyzing high-dimensional GWAS summary statistics presents logistical and computational challenges. In this talk, we introduce the BIGA platform (http://bigagwas.org/), a website that offers unified data analysis pipelines and centralized data resources. We have developed a framework that implements statistical genetics tools on a cloud computing platform, integrated with extensive curated GWAS datasets. Furthermore, we discuss our recent theoretical analyses of the LD score regression (LDSC), a widely-used method for inferring heritability and genetic correlation using GWAS summary statistics. We provide theoretical guarantees for LDSC-based estimators by explicitly modeling the block-wise dependence pattern of high-dimensional GWAS data. These analyses are joint work with Fei Xue and Yujue Li.