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Variant prioritization by genomic data fusion

Variant prioritization by genomic data fusion

This video was recorded at Marie Curie Initial Training Network on Machine Learning for Personalized Medicine (MLPM) 1st Summer School, Tübingen, 2013. NGS has rapidly increased our ability to discover the cause of many previously unresolved rare monogenic disorders by sequencing rare exomic variation. However, after standard filtering against nonsynonymous single nucleotide variants (nSNVs) and loss-of-function mutations that are not present in healthy populations or unaffected samples, many potential candidate mutations are often retained and we need predictive methods to prioritize variants for further validation. Several computational methods have been proposed that take into account biochemical, evolutionary and structural properties of mutations to assess their potential... Show More
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