Bioinformatics Seminar
Time:
Venue: Na
23 May 2017
NaInsights from simulating deep mutational scanning datasets
Alan RubinWEHI Bioinformatics
Although high-throughput DNA sequencing has rapidly expanded catalogues of normal and disease-associated variation ; the functional consequences of most mutations are unknown. In deep mutational scanning ; selection for protein function applied to a library of protein variants is combined with high-throughput DNA sequencing ; allowing direct measurement of the activity of hundreds of thousands of variants of the protein easily and cheaply. This approach helps to bridge the gap between variant identification and interpretation ; enabling researchers to elucidate sequence-function relationships at high resolution. Alan will present a novel method for simulating deep mutational scanning data and its potential utility in interpreting functional scores assigned to individual variants. He will also discuss applying deep mutational scanning more broadly to the problem of variant effect prediction ; where deep mutational scanning has been shown to outperform existing approaches such as SIFT/PolyPhen.;;;