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Predicting the origin of stains from whole miRNome massively parallel sequencing data
Guro Dørum1, Sabrina Ingold1, Erin Hanson2
1Zurich Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland.
Abstract:
In this study, we have screened the six most relevant forensic body fluids / tissues, namely blood, semen, saliva, vaginal secretion, menstrual blood and skin, for miRNAs using a whole miRNome massively parallel sequencing approach. We applied partial least squares (PLS) and linear discriminant analysis (LDA) to predict body fluids based on the expression of the miRNA markers. We estimated the prediction accuracy for models including different subsets of miRNA markers to identify the minimum number of markers needed for sufficient prediction performance. For one selected model consisting of 9 miRNA markers we calculated their importance for prediction of each of the six different body fluid categories.
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