Since repetitive sequences in the human genome called short tandem repeats (STRs) are used in human identification for forensic purposes and interpretation of DNA profiles generated using STRs is often problematic because of uncertainty in the number of contributors to the sample, the current project developed a computational method called NOCIt, which calculates the a posteriori probability (APP) on the number of contributors.
NOCIt works on single-source calibration data consisting of known genotypes to compute the APP for an unknown sample. The method takes into account signal peak heights, population allele frequencies, allele dropout and stutter—a commonly occurring PCR artifact. Researchers tested the performance of NOCIt using 278 experimental and 40 simulated DNA mixtures consisting of one to five contributors with total DNA mass from 0.016 to 0.25 ng. NOCIt correctly identified the number of contributors in 83 percent of the experimental samples and in 85 percent of the simulated mixtures, while the accuracy of the best pre-existing method to determine the number of contributors was 72 percent for the experimental samples and 73 percent for the simulated mixtures. Moreover, NOCIt calculated the APP for the true number of contributors to be at least 1 percent in 95 percent of the experimental samples and in all the simulated mixtures. (publisher abstract modified)