Patent ID: 11861491
Assignee: ILLUMINA, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A system comprising:
one or more processors; and
a non-transitory computer readable medium comprising a trained convolutional neural network-based pathogenicity classifier that predicts pathogenicity of promoter region single nucleotide variants (abbreviated pSNVs) and instructions that, when executed by the one or more processors, cause the system to perform operations comprising:
accessing an input promoter sequence with reference bases at a plurality of base positions comprising one or more observed pSNV positions corresponding to pSNVs identified within a sample genomic dataset;
processing the input promoter sequence through one or more layers of the trained convolutional neural network-based pathogenicity classifier to generate an alternative representation of the input promoter sequence, the one or more layers of the trained convolutional neural network-based pathogenicity classifier:
trained utilizing input promoter training sequences comprising one or more observed pSNVs sampled from pSNVs identified within the sample genomic dataset and one or more unobserved pSNVs sampled from a pool of substitutionally generated pSNVs at base positions for which pSNVs are not identified within the sample genomic dataset; and
comprising one or more groups of residual blocks, each residual block comprising one or more of a batch normalization layer, a rectified linear unit (ReLU), an atrous convolution layer, or a residual connection; and
processing the alternative representation to generate, for each base position in the input promoter sequence, pathogenicity predictions that classify each of three base variations from a corresponding reference base as benign or pathogenic.