What is a stochastic threshold in STR interpretation and why is it important?

What is a stochastic threshold in STR interpretation and why is it important?

• A. A measure of peak height that indicates all peaks are reliable.
• B. A minimum peak height below which allele calls are unreliable due to stochastic effects; informs replication or cautious interpretation.
• C. A threshold for the minimum DNA quantity required for extraction.
• D. A criterion for deciding whether to run probabilistic genotyping.

Answer: (B)

In STR interpretation, the stochastic threshold is a peak-height cutoff used to separate reliable allele calls from signals that may arise from random sampling effects when DNA input is very low. At low template levels, PCR amplification becomes stochastic, so one allele in a heterozygous locus can drop out or be underrepresented. If a peak falls below this threshold, the call is considered unreliable because it could be due to allelic dropout rather than a true genotype. In such cases, analysts may require replication, re-extraction, or more cautious interpretation to avoid false conclusions. Peaks above the threshold are treated as more trustworthy, though other artifacts like stutter or baseline noise are still considered. This threshold is lab-specific and depends on the instrument, kit, and run conditions, which is why it’s used to guide whether a result should be replicated or interpreted with caution.

In STR interpretation, the stochastic threshold is a peak-height cutoff used to separate reliable allele calls from signals that may arise from random sampling effects when DNA input is very low. At low template levels, PCR amplification becomes stochastic, so one allele in a heterozygous locus can drop out or be underrepresented. If a peak falls below this threshold, the call is considered unreliable because it could be due to allelic dropout rather than a true genotype. In such cases, analysts may require replication, re-extraction, or more cautious interpretation to avoid false conclusions. Peaks above the threshold are treated as more trustworthy, though other artifacts like stutter or baseline noise are still considered. This threshold is lab-specific and depends on the instrument, kit, and run conditions, which is why it’s used to guide whether a result should be replicated or interpreted with caution.