Variant prediction and annotation

Genetic difference between and within species drive how we evolve, but also what causes malfunctioning of genes and phenotypic differences. Genetic differences include SNPs as well as larger structural variations. But how to detect variants reliably? And, what if a genome is polyploid, can you detect variants for each of the alleles? Furthermore, not all genetic variants do have a functional impact. Some even might be beneficial. Simple effects, like introducing a stop codon, are easy to detect. But how to predict the more complex effect? DBL develops tools to predict and annotate  genetic variations in these different contexts.

Our research directions include:

• Reliable variant calling
• Multinuclear/Allele specific variant calling
• Tissue specific somatic variant detection
• Calling variants from RNA
• Machine learning approaches towards predicting variant effects, such as whether they are deleterious or protective