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Computer Automation of STR Scoring for Forensic Databases

M.W. Perlin, "Computer automation of STR scoring for forensic databases", First International Conference on Forensic Human Identification in the Millennium, London, UK, 26-Oct-1999.


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PowerPoint presentation and handout for the International Conference on Forensic Human Identification in the Millennium 1999 talk.

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Abstract

Forensic databases are becoming an increasingly valuable law enforcement tool for convicting repeat offenders and exonerating the innocent. However, constructing such databases is quite laborious. After generating STR profiles in the lab, people expend even greater effort visually reviewing the data before it enters the database. All artifacts must be detected, and no error can be tolerated. With millions of samples to analyze every year, this has become a formidable task.

We have developed software analysis methods that can automate this data review and potentially eliminate 90% of the work. Our fully automated TrueAllele system inputs raw fluorescent DNA sequencer gel files, processes the gel image (separating colors, tracking and sizing lanes), and analyzes the STR experiments (quantitating and sizing peaks, comparing with ladder peaks, calling alleles). For each allele call, TrueAllele assigns a quality score and applies artifact detection rules. These quality checks enable a user to focus on just the 5%-10% of suspect data, thereby eliminating most of the review effort.

We are currently developing more powerful extensions to TrueAllele for advanced forensic processing. TrueAllele can already read data from any DNA sequencer, and process it on any computer. Our immediate goal is to have TrueAllele replicate much of the reasoning of the forensic database analyst, and present its focused conclusions visually, rapidly and intuitively. Longer-term, we expect TrueAllele to develop into an intelligent casework assistant.