ArticlePloS one2009
An information gap in DNA evidence interpretation.
Article in PloS one, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
11 citing papers in PubMed.
- Article
- Article
- Open practices in our science and our courtrooms.Trends in genetics : TIG · 2022Article
- Validating TrueAlleleJournal of forensic sciences · 2020Article
- Efficient construction of match strength distributions for uncertain multi-locus genotypes.Heliyon · 2018Article
- Four model variants within a continuous forensic DNA mixture interpretation framework: Effects on evidential inference and reporting.PloS one · 2018Article
- Lab Retriever: a software tool for calculating likelihood ratios incorporating a probability of drop-out for forensic DNA profiles.BMC bioinformatics · 2015Article
- Inclusion probability for DNA mixtures is a subjective one-sided match statistic unrelated to identification information.Journal of pathology informatics · 2015Article
- TrueAllele casework on Virginia DNA mixture evidence: computer and manual interpretation in 72 reported criminal cases.PloS one · 2014Article
- New York State TrueAllele ® casework validation study.Journal of forensic sciences · 2013Article
- Forensic trace DNA: a review.Investigative genetics · 2010Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Forensic DNA evidence often contains mixtures of multiple contributors, or is present in low template amounts. The resulting data signals may appear to be relatively uninformative when interpreted using qualitative inclusion-based methods. However, these same data can yield greater identification information when interpreted by computer using quantitative data-modeling methods. This study applies both qualitative and quantitative interpretation methods to a well-characterized DNA mixture and dilution data set, and compares the inferred match information. The results show that qualitative interpretation loses identification power at low culprit DNA quantities (below 100 pg), but that quantitative methods produce useful information down into the 10 pg range. Thus there is a ten-fold information gap that separates the qualitative and quantitative DNA mixture interpretation approaches. With low quantities of culprit DNA (10 pg to 100 pg), computer-based quantitative interpretation provides greater match sensitivity.
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Registered trials
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