Publication: Predicting the origin of stains from whole miRNome massively parallel sequencing data
Predicting the origin of stains from whole miRNome massively parallel sequencing data
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Dørum, G., Ingold, S., Hanson, E., Ballantyne, J., Russo, G., Aluri, S., Snipen, L., & Haas, C. (2019). Predicting the origin of stains from whole miRNome massively parallel sequencing data. Forensic Science International. Genetics, 40, 131–139. https://doi.org/10.1016/j.fsigen.2019.02.015
Abstract
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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 pre
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- Dørum, Guro
- Ingold, Sabrina
- Hanson, Erin
- Ballantyne, Jack
- Russo, Giancarlo
- Aluri, Sirisha
- Snipen, Lars
- Haas, Cordula
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Dørum, G., Ingold, S., Hanson, E., Ballantyne, J., Russo, G., Aluri, S., Snipen, L., & Haas, C. (2019). Predicting the origin of stains from whole miRNome massively parallel sequencing data. Forensic Science International. Genetics, 40, 131–139. https://doi.org/10.1016/j.fsigen.2019.02.015
