(a) obtaining, in electronic format, one or more training subject datasets, each training subject dataset comprising a corresponding training variant allele frequency of each respective training single nucleotide variant in a plurality of training single nucleotide variants;

(b) training a computational neural network based on the one or more training subject datasets, wherein the computational neural network comprises a pre-trained convolutional neural network and an untrained classifier;

(c) obtaining, in electronic format, a test subject dataset comprising a corresponding test variant allele frequency of each respective test single nucleotide variant in a plurality of test single nucleotide variants; and

(d) determining the contamination status for the test biological sample based on the trained computational neural network and the test subject dataset.