The described method is accomplished by using a dynamic locus and sample specific analytical threshold and a machine learning-derived probabilistic artifact detection model. The system produced an allele detection accuracy of 97.2 percent, an 11.4-percent increase from the lowest static threshold (50 RFU), with a low incidence of incorrectly identified artifacts (0.79 percent). This adaptive method outperformed static thresholds in the retention of allelic information content at minimal cost. (publisher abstract modified)
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