30-Sep-2022

Why error rates are needed for reliable DNA evidence

A match statistic measures the strength of DNA evidence. Evidence can change our belief in whether someone was at a crime scene; the match strength quantifies that change. Positive (logarithmic) numbers support the belief, negative ones militate against it, while values near zero give little information either way.

An error rate provides a frequency context for LR match information. Suppose the LR is 100. What is the chance that someone who didn't leave their DNA matches as strongly? Is it one in a thousand? Or is it one in a million? That probability – the false positive error rate – informs a juror. It tells them, "How often might this DNA match evidence falsely implicate me?"

Without an error rate, there is no frequency context to tell us how often a DNA match may be false. An "inconclusive" statement means no reported DNA result. Unethical trial lawyers sometimes try to twist this non-result into fake "evidence" of guilt.

Santa Clara County Judge Kelley Paul and Cybergenetics CEO Dr. Mark Perlin exposed this illogical ploy at the February American Academy of Forensic Sciences conference. You can watch their myth-busting presentation "Making something out of nothing: the inconclusive fallacy" on YouTube.

Cybergenetics' accurate match statistics and error rates overcome the "inconclusive" fallacy. In criminal cases from California to New York, TrueAllele analyst testimony helps block unscientific injustice.