Abstract
Chemical and staining methods, immunochromatography, spectroscopy, RNA expression or methylation patterns, do not allow to determine the nature of the biological material with certainty. However, to our knowledge, there are few forensic scientists that assess the value of such test results using a probabilistic approach. This is surprising as it would allow account for false positives and false negatives and avoid misleading conclusions.In this paper, we developed three Bayesian Networks (BNs) to assess the presence of blood, saliva and sperm in the recovered material and combine potentially contradictory observations. The approach was successfully tested using 188 traces from proficiency tests. We have implemented an online user-friendly application (https://forensic-genetic.shinyapps.io/BodyFluidsApp/) that allows forensic scientists to assess the value of their results without having to build Bayesian Networks themselves. They can also input their own data, use the application to identify a potential lack of knowledge and report their conclusions regarding the presence of sperm, blood or/and saliva considering uncertainty.
Highlights
The characterization of the nature of biological fluids can be important for the investigation
Node 2 (Nature) of saliva and sperm Bayesian Networks (BNs) When considering the probability of a positive result given the alternative proposition, we typically consider the possibility of false positives
Forensic scientists need to account for the possibility of false positives and false negatives, when reporting their findings re garding the nature of a biological material
Summary
The characterization of the nature of biological fluids (e.g., blood, saliva or sperm) can be important for the investigation. False negatives as well as false positives, including misrecognition of type of cell, are known to occur We define all these tests as presumptive in this paper. Further more, few forensic scientists use BNs. We believe that possible reasons for this could be: the lack of an accessible tool, the difficulty of integrating one’s own data into the models and the lack of examples of how one can report such results. To present three examples of BNs that allow to make inferences on the possible presence of respectively blood, saliva and sperm. To propose a free online tool (i.e., Shiny application) for implementing the approach (https://forensic-genetic.shinyapps.io/ BodyFluidsApp/) This user-friendly interface allows to in tegrate users’ data within the Bayesian network that works be hind the scene. We conclude the section by showing, using sensitivity analysis, how this application helps assessing the impact paucity of data can have on the value of the results
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