Aashish N. Adhikari

The paper assesses improvements in genomic variant classification accuracy over time in ClinVar and HGMD by analyzing misclassification rates in inborn errors of metabolism across ancestry groups.

The paper uses primate genetic data to predict human variant pathogenicity with a deep learning classifier trained on 4.3 million common missense variants.

The paper evaluates how parameter choices affect variant interpretation pipelines by systematically perturbing parameters and shows that certain choices significantly impact sensitivity and specificity.

This study evaluates the quality of exome sequencing from DNA extracted from dried blood spots (DBS) and finds it comparable to whole blood, with similar variant calling accuracy.