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Forensic Body Fluid Identification by Analysis of Multiple RNA Markers Using NanoString Technology
Genomics & Informatics ; : 277-281, 2013.
Artigo em Inglês | WPRIM | ID: wpr-84016
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.
Assuntos

Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Assunto principal: Saliva / Sêmen / Líquidos Corporais / RNA / Modelos Logísticos / Estimulação Elétrica Nervosa Transcutânea / Reação em Cadeia da Polimerase Tipo de estudo: Estudo diagnóstico / Fatores de risco Idioma: Inglês Revista: Genomics & Informatics Ano de publicação: 2013 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Assunto principal: Saliva / Sêmen / Líquidos Corporais / RNA / Modelos Logísticos / Estimulação Elétrica Nervosa Transcutânea / Reação em Cadeia da Polimerase Tipo de estudo: Estudo diagnóstico / Fatores de risco Idioma: Inglês Revista: Genomics & Informatics Ano de publicação: 2013 Tipo de documento: Artigo