What can help you determine the significance of genetic variants?

Resources

The SCN5A Variant Browser (link)

In collaboration with Vanderbilt Center for Arrhythmia Research and Therapeutics (VanCART), the SCN5A variant browser is derived from a dataset described in Kroncke and Glazer et al. 2018, Circulation: Genomic and Precision Medicine. The data are curated from a comprehensive literature review from papers written about SCN5A (or Nav1.5, the protein product of SCN5A) up to December 2017. Scripts and data can be found on GitHub (link)


Predicting changes in NaV1.5 (SCN5A) and KV7.1 (KCNQ1) function

We leveraged our previously collected NaV1.5 (SCN5A) and KV7.1 (KCNQ1) datasets to assess the ability of structure- and sequence-based predictive features to predict changes in channel function. Scripts and data can be found on GitHub (link)


A Bayesian method to estimate disease penetrance from genetic variant properties

We leveraged our previously collected NaV1.5 (SCN5A) dataset, supplemented with variants published within the last year, to assess the ability of functional, structural, and sequence-based predictive features to estimate Brugada syndrome penetrance. Scripts and data can be found on GitHub (link)

Deep Mutational Scan of KCNH2

We developed a method to assay the trafficking perturbation induced by missense variants in KCNH2 in high-throughput, capable of collecting these data for 1,000s of variants at a time. Scripts and data used can be found on GitHub (link)