Neural networks complement hidden Markov models in an ensemble for genotype imputation

CrossBlend combines hidden Markov model imputation with ImputeMLP, a chunked multilayer-perceptron imputer trained on the typed SNPs of an array. Because the network’s errors differ from those of the HMM methods, the ensemble improves genotype imputation accuracy, with gains that grow with the size of the reference panel.

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