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CEESIt: A computational tool for the interpretation of STR mixtures
Harish Swaminathan1, Abhishek Garg2, Catherine M Grgicak3
1Center for Computational and Integrative Biology, Rutgers University, Camden, NJ 08102, USA.
Forensic Science International. Genetics
|March 7, 2016
Summary
The CEESIt method offers a fully continuous model for calculating likelihood ratios (LR) and their distributions in forensic DNA analysis. This approach improves the robustness of match strength assessment, incorporating factors like dropout and noise for more reliable results.
Area of Science:
- Forensic Science
- Genetics
- Biostatistics
Background:
- Likelihood ratio (LR) is crucial in forensic DNA interpretation to quantify match strength.
- Existing methods (binary, semi-continuous) do not fully utilize electropherogram data.
- Fully continuous methods offer enhanced data utilization, including peak heights.
Purpose of the Study:
- Introduce CEESIt, a novel method for calculating LR and its distribution using a fully continuous model.
- Incorporate key forensic considerations like dropout, noise, and stutter into LR calculations.
- Evaluate the performance of CEESIt on complex DNA mixtures and assess its repeatability.
Main Methods:
- Developed CEESIt, a fully continuous probabilistic model for LR and LR distribution calculation.
- Incorporated dropout, noise, and stutter (forward/reverse) into the CEESIt model.
- Utilized single-source samples for calibration and tested on 303 mixed DNA samples (1-3 contributors).
Main Results:
- CEESIt successfully calculated LR, LR distribution, and p-values for complex DNA mixtures.
- Low template DNA mass from contributors resulted in smaller LRs.
- P-values decreased as LR increased, with p-values ≤ 10⁻⁹ for LR > 10⁸; results were repeatable.
Conclusions:
- CEESIt provides a robust, fully continuous approach to LR calculation and distribution analysis in forensic DNA.
- The method effectively handles complex samples and provides valuable insights into match strength and potential errors.
- CEESIt demonstrates repeatability and offers a significant advancement for complex DNA mixture interpretation.
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