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


Dørum, Guro; Ingold, Sabrina; Hanson, Erin; Ballantyne, Jack; Russo, Giancarlo; Aluri, Sirisha; Snipen, Lars; Haas, Cordula (2019). Predicting the origin of stains from whole miRNome massively parallel sequencing data. Forensic Science International. Genetics, 40:131-139.

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.

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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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Legal Medicine
Dewey Decimal Classification:510 Mathematics
Scopus Subject Areas:Health Sciences > Pathology and Forensic Medicine
Life Sciences > Genetics
Uncontrolled Keywords:Pathology and Forensic Medicine, Genetics
Language:English
Date:1 May 2019
Deposited On:16 Dec 2019 11:39
Last Modified:22 Apr 2020 21:13
Publisher:Elsevier
ISSN:1872-4973
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.fsigen.2019.02.015
PubMed ID:30818157
Project Information:
  • : FunderFP7
  • : Grant ID285487
  • : Project TitleEUROFORGEN-NOE - EUROPEAN FORENSIC GENETICS Network of Excellence

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