80
(4) Under what circumstances—and why—does the method produce results (random inclusion
probabilities) that differ substantially from those produced by other methods?
A number of papers have been published that analyze known mixtures in order to address some of these
issues.
213
Two points should be noted about these studies. First, most of the studies evaluating software
packages have been undertaken by the software developers themselves. While it is completely appropriate for
method developers to evaluate their own methods, establishing scientific validity also requires scientific
evaluation by other scientific groups that did not develop the method. Second, there have been few
comparative studies across the methods to evaluate the differences among them—and, to our knowledge, no
comparative studies conducted by independent groups.
214
Most importantly, current studies have adequately explored only a limited range of mixture types (with respect
to number of contributors, ratio of minor contributors, and total amount of DNA). The two most widely used
methods (STRMix and TrueAllele) appear to be reliable within a certain range, based on the available evidence
and the inherent difficulty of the problem.
215
Specifically, these methods appear to be reliable for three-person
mixtures in which the minor contributor constitutes at least 20 percent of the intact DNA in the mixture and in
which the DNA amount exceeds the minimum level required for the method.
216
213
For example: Perlin, M.W., Hornyak, J.M., Sugimoto, G., and K.W.P. Miller. “TrueAllele genotype identification on DNA
mixtures containing up to five unknown contributors.” Journal of Forensic Sciences, Vol. 60, No. 4 (2015): 857-868;
Greenspoon S.A., Schiermeier-Wood L., and B.C. Jenkins. “Establishing the limits of TrueAllele® Casework: A validation
study.” Journal of Forensic Sciences. Vol. 60, No. 5 (2015):1263–76; Bright, J.A., Taylor, D., McGovern, C., Cooper, S., Russell,
L., Abarno, D., and J.S. Buckleton. “Developmental validation of STRmix
TM
, expert software for the interpretation of forensic
DNA profiles.” Forensic Science International: Genetics. Vol. 23 (2016): 226-39; Bright, J-A., Taylor D., Curran, J.S., and J.S.
Buckleton. “Searching mixed DNA profiles directly against profile databases.” Forensic Science International: Genetics. Vol. 9
(2014):102-10; Taylor D., Buckleton J, and I. Evett. “Testing likelihood ratios produced from complex DNA profiles.” Forensic
Science International: Genetics. Vol. 16 (2015): 165-171; Taylor D. and J.S. Buckleton. “Do low template DNA profiles have
useful quantitative data?” Forensic Science International: Genetics, Vol. 16 (2015): 13-16.
214
Bille, T.W., Weitz, S.M., Coble, M.D., Buckleton, J., and J.A. Bright. “Comparison of the performance of different models
for the interpretation of low level mixed DNA profiles.” Electrophoresis. Vol. 35 (2014): 3125–33.
215
The interpretation of DNA mixtures becomes increasingly challenging as the number of contributors increases. See, for
example: Taylor D., Buckleton J, and I. Evett. “Testing likelihood ratios produced from complex DNA profiles.” Forensic
Science International: Genetics. Vol. 16 (2015): 165-171; Bright, J.A., Taylor, D., McGovern, C., Cooper, S., Russell, L., Abarno,
D., and J.S. Buckleton. “Developmental validation of STRmix
TM
, expert software for the interpretation of forensic DNA
profiles.” Forensic Science International: Genetics. Vol. 23 (2016): 226-39; Bright, J-A., Taylor D., Curran, J.S., and J.S.
Buckleton. “Searching mixed DNA profiles directly against profile databases.” Forensic Science International: Genetics. Vol. 9
(2014):102-10; Bieber, F.R., Buckleton, J.S., Budowle, B., Butler, J.M., and M.D. Coble. “Evaluation of forensic DNA mixture
evidence: protocol for evaluation, interpretation, and statistical calculations using the combined probability of inclusion.”
BMC Genetics. bmcgenet.biomedcentral.com/articles/10.1186/s12863-016-0429-7
.
216
Such three-person samples involving similar proportions are more straightforward to interpret owing to the limited
number of alleles and relatively similar peak height. The methods can also be reliably applied to single-source and simple-
mixture samples, provided that, in cases where the two contributions cannot be separated by differential extraction, the
proportion of the minor contributor is not too low (e.g., at least 10 percent).