Forensic comparison of soils by bacterial community DNA profiling

This preliminary investigation has shown that a soil microbial community DNA profile can be obtained from the small sample of soil recovered from the sole of a shoe, and from soil stains on clothing. We have also shown that these profiles are representative of the site of collection and therefore could potentially be used as associative evidence to prove a link between suspects and crime scenes. Soil community profiles were obtained using the T-RFLP fingerprinting method that uses fluorescent primer technology and semi-automated analysis techniques similar to those used in human DNA profiling in forensic laboratories.     

Addressing the National Academy of Sciences' challenge: a method for statistical pattern comparison of striated tool marks

In February 2009, the National Academy of Sciences published a report entitled "Strengthening Forensic Science in the United States: A Path Forward." The report notes research studies must be performed to "…understand the reliability and repeatability…" of comparison methods commonly used in forensic science. Numerical classification methods have the ability to assign objective quantitative measures to these words. In this study, reproducible sets of ideal striation patterns were made with nine slotted screwdrivers, encoded into high-dimensional feature vectors, and subjected to multiple statistical pattern recognition methods. The specific methods employed were chosen because of their long peer-reviewed track records, widespread successful use for both industry and academic applications, rely on few assumptions on the data's underlying distribution, can be accompanied by standard confidence levels, and are falsifiable. For PLS-DA, correct classification rates of 97% or higher were achieved by retaining only eight dimensions (8D) of data. PCA-SVM required even fewer dimensions, 4D, for the same level of performance. Finally, for the first time in forensic science, it is shown how to use conformal prediction theory to compute identifications of striation patterns at a given level of confidence.