Fig. 1

Data preparation and model development steps for MetaRNN. First, the target variant and affect codon were identified, e.g., g.1022225G>T. Second, the flanking sequences were retrieved as well as all possible alternative alleles, as illustrated on the nucleotides to the right of the up-pointing arrow. Third, only alleles that result in a missense variant were kept, and annotation scores were averaged across these alleles within the same locus. For example, the annotation scores for variants g.1022230A>T and g.1022230A>C will be averaged, to get the locus-specific annotations. Lastly, the model will be trained using the annotations for context variants and annotations for the target variant