Predicting the origin of stains from whole miRNome massively parallel sequencing data

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.

Keywords: Body fluid identification; Forensic science; Linear discriminant analysis LDA; Massively parallel sequencing MPS; Partial least squares PLS; Probabilistic method; miRNA.