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Forensic Body Fluid Identification by Analysis of Multiple RNA Markers Using NanoString Technology
Genomics & Informatics ; : 277-281, 2013.
Article en En | WPRIM | ID: wpr-84016
Biblioteca responsable: WPRO
ABSTRACT
RNA analysis has become a reliable method of body fluid identification for forensic use. Previously, we developed a combination of four multiplex quantitative PCR (qRT-PCR) probes to discriminate four different body fluids (blood, semen, saliva, and vaginal secretion). While those makers successfully identified most body fluid samples, there were some cases of false positive and negative identification. To improve the accuracy of the identification further, we tried to use multiple markers per body fluid and adopted the NanoString nCounter system instead of a multiplex qRT-PCR system. After measuring tens of RNA markers, we evaluated the accuracy of each marker for body fluid identification. For body fluids, such as blood and semen, each body fluid-specific marker was accurate enough for perfect identification. However, for saliva and vaginal secretion, no single marker was perfect. Thus, we designed a logistic regression model with multiple markers for saliva and vaginal secretion and achieved almost perfect identification. In conclusion, the NanoString nCounter is an efficient platform for measuring multiple RNA markers per body fluid and will be useful for forensic RNA analysis.
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Texto completo: 1 Índice: WPRIM Asunto principal: Saliva / Semen / Líquidos Corporales / ARN / Modelos Logísticos / Estimulación Eléctrica Transcutánea del Nervio / Reacción en Cadena de la Polimerasa Tipo de estudio: Diagnostic_studies / Risk_factors_studies Idioma: En Revista: Genomics & Informatics Año: 2013 Tipo del documento: Article
Texto completo: 1 Índice: WPRIM Asunto principal: Saliva / Semen / Líquidos Corporales / ARN / Modelos Logísticos / Estimulación Eléctrica Transcutánea del Nervio / Reacción en Cadena de la Polimerasa Tipo de estudio: Diagnostic_studies / Risk_factors_studies Idioma: En Revista: Genomics & Informatics Año: 2013 Tipo del documento: Article