Estimating allele dropout probabilities by logistic regression: Assessments using Applied Biosystems 3500xL and 3130xl Genetic Analyzers with various commercially available human identification kits. (March 2016)
- Record Type:
- Journal Article
- Title:
- Estimating allele dropout probabilities by logistic regression: Assessments using Applied Biosystems 3500xL and 3130xl Genetic Analyzers with various commercially available human identification kits. (March 2016)
- Main Title:
- Estimating allele dropout probabilities by logistic regression: Assessments using Applied Biosystems 3500xL and 3130xl Genetic Analyzers with various commercially available human identification kits
- Authors:
- Inokuchi, Shota
Kitayama, Tetsushi
Fujii, Koji
Nakahara, Hiroaki
Nakanishi, Hiroaki
Saito, Kazuyuki
Mizuno, Natsuko
Sekiguchi, Kazumasa - Abstract:
- Graphical abstract: Highlights: Allele dropout probabilities of 3500xL and 3130 xl evaluated by logistic analysis. The analytical thresholds were lower than values recommended by the manufacturer. Standards of the allele dropout probabilities from the peak heights were shown. Abstract: Phenomena called allele dropouts are often observed in crime stain profiles. Allele dropouts are generated because one of a pair of heterozygous alleles is underrepresented by stochastic influences and is indicated by a low peak detection threshold. Therefore, it is important that such risks are statistically evaluated. In recent years, attempts to interpret allele dropout probabilities by logistic regression using the information on peak heights have been reported. However, these previous studies are limited to the use of a human identification kit and fragment analyzer. In the present study, we calculated allele dropout probabilities by logistic regression using contemporary capillary electrophoresis instruments, 3500xL Genetic Analyzer and 3130 xl Genetic Analyzer with various commercially available human identification kits such as AmpFℓSTR® Identifiler® Plus PCR Amplification Kit. Furthermore, the differences in logistic curves between peak detection thresholds using analytical threshold (AT) and values recommended by the manufacturer were compared. The standard logistic curves for calculating allele dropout probabilities from the peak height of sister alleles were characterized. TheGraphical abstract: Highlights: Allele dropout probabilities of 3500xL and 3130 xl evaluated by logistic analysis. The analytical thresholds were lower than values recommended by the manufacturer. Standards of the allele dropout probabilities from the peak heights were shown. Abstract: Phenomena called allele dropouts are often observed in crime stain profiles. Allele dropouts are generated because one of a pair of heterozygous alleles is underrepresented by stochastic influences and is indicated by a low peak detection threshold. Therefore, it is important that such risks are statistically evaluated. In recent years, attempts to interpret allele dropout probabilities by logistic regression using the information on peak heights have been reported. However, these previous studies are limited to the use of a human identification kit and fragment analyzer. In the present study, we calculated allele dropout probabilities by logistic regression using contemporary capillary electrophoresis instruments, 3500xL Genetic Analyzer and 3130 xl Genetic Analyzer with various commercially available human identification kits such as AmpFℓSTR® Identifiler® Plus PCR Amplification Kit. Furthermore, the differences in logistic curves between peak detection thresholds using analytical threshold (AT) and values recommended by the manufacturer were compared. The standard logistic curves for calculating allele dropout probabilities from the peak height of sister alleles were characterized. The present study confirmed that ATs were lower than the values recommended by the manufacturer in human identification kits; therefore, it is possible to reduce allele dropout probabilities and obtain more information using AT as the peak detection threshold. … (more)
- Is Part Of:
- Legal medicine. Volume 19(2016)
- Journal:
- Legal medicine
- Issue:
- Volume 19(2016)
- Issue Display:
- Volume 19, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 19
- Issue:
- 2016
- Issue Sort Value:
- 2016-0019-2016-0000
- Page Start:
- 77
- Page End:
- 82
- Publication Date:
- 2016-03
- Subjects:
- Allele dropout probability -- Logistic regression -- 3500xL Genetic Analyzer -- Analytical threshold
Medical jurisprudence -- Periodicals
Forensic Medicine -- Periodicals
Médecine légale -- Périodiques
Medical jurisprudence
Periodicals
614.1 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13446223 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.legalmed.2015.07.006 ↗
- Languages:
- English
- ISSNs:
- 1344-6223
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5181.329970
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