Prediction of spurious HLA class II typing results using probabilistic classification.

Abstract excerpt

While modern high-throughput sequence-based HLA genotyping methods generally provide highly accurate typing results, artefacts may nonetheless arise for numerous reasons, such as sample contamination, sequencing errors, read misalignments, or PCR amplification biases. To help detecting spurious typing results, we tested the performance of two probabilistic classifiers (binary logistic regression and random forest...

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