Expected net gain data of low-template DNA analyses.
Simone Gittelson1, Carolyn R Steffen1, Michael D Coble1
1National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD 20899, United States.
Data in Brief
|June 23, 2016
Summary
Stochastic effects in low-template DNA analysis can alter results. This study quantifies the expected net gain (ENG) of single versus replicate DNA amplifications to optimize forensic analysis strategies.
Area of Science:
- Forensic Science
- Genetics
- Decision Theory
Background:
- Low-template DNA (ltDNA) analysis is prone to stochastic effects, leading to potential genotype discrepancies.
- Electropherograms (EPGs) may not accurately reflect the true DNA profile due to these random variations.
- Decision theory offers a framework to evaluate the utility of DNA analyses.
Purpose of the Study:
- To present data on the expected net gain (ENG) for low-template DNA analyses.
- To compare the ENG of single amplification versus replicate amplifications.
- To evaluate the ENG of a second replicate analysis conditional on the first analysis result.
Main Methods:
- Utilized a probabilistic and decision-theoretic model to calculate ENG.
- Employed AmpFlSTR Identifiler Plus and Promega PowerPlex 16 HS amplification kits.
- Used an ABI 3130xl genetic sequencer and GeneMapper ID-X software for analysis.
Main Results:
- Presented data quantifying the ENG for single, double, and sequential replicate ltDNA analyses.
- Provided supplementary data to a prior study on the decision-theoretic approach to ltDNA analysis.
- The data supports informed decisions regarding the number of DNA amplifications in forensic casework.
Conclusions:
- The study quantifies the expected net gain (ENG) for different low-template DNA analysis strategies.
- Decision-theoretic modeling aids in optimizing forensic DNA testing protocols.
- Informed decisions on replicate amplifications can improve the reliability of DNA profiling.
