Neur-Ally: a deep learning model for regulatory variant prediction based on genomic and epigenomic features in brain and its validation in certain neurological disorders.

The significant gene–variant pair files (v8) of the following samples belonging to the nervous system from GTEx portal were used for extracting neurological condition-specific eQTL positive variant set: “Cerebellum,” “Nucleus accumbens basal ganglia,” “Cortex,” “Caudate basal ganglia,” “Cerebellar Hemisphere,” “Anterior cingulate cortex BA24,” “Amygdala,” “Spinal cord cervical C-1,” “Hypothalamus,” “Substantia nigra,” “Frontal Cortex BA9,” “Hippocampus,” and “Putamen basal ganglia.” Top 1000 hits from each sample were used for the predictions, and after stringent filtering, 169 highly significant regulatory SNPs were predicted by the model ( Supplementary Table S3 ).

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