Lab Retriever: a software tool for calculating likelihood ratios incorporating a probability of drop-out for forensic DNA profiles

BMC Bioinformatics

Keith Inman¹  Norah Rudin⁶  Ken Cheng³  Chris Robinson⁴  Adam Kirschner⁵  Luke Inman-Semerau⁷  Kirk E. Lohmueller² 

[1] Department of Criminal Justice Administration, California State University, East Bay, 25800 Carlos Bee Boulevard, Hayward 94542, CA, USA

[2] Department of Ecology and Evolutionary Biology, University of California, Los Angeles, 621 Charles E. Young Dr. South, Los Angeles 90095-1606, CA, USA

[3] 1224 Burnham Dr, San Jose 95132, CA, USA

[4] 2854 Marsh St, Los Angeles 90039, CA, USA

[5] 401 East 86th St., Apt 12H, New York 10028, NY, USA

[6] 650 Castro Street, Suite 120-404, Mountain View 94041, CA, USA

[7] 604 Lochmoor Ct, Danville 94526, CA, USA

关键词: Drop-out;    Probabilistic;    Forensic DNA;    Likelihood ratio;   

Others  :  1229454
DOI  :  10.1186/s12859-015-0740-8

 received in 2015-01-13, accepted in 2015-09-12,  发布年份 2015

【 摘 要 】

Background

Technological advances have enabled the analysis of very small amounts of DNA in forensic cases. However, the DNA profiles from such evidence are frequently incomplete and can contain contributions from multiple individuals. The complexity of such samples confounds the assessment of the statistical weight of such evidence. One approach to account for this uncertainty is to use a likelihood ratio framework to compare the probability of the evidence profile under different scenarios. While researchers favor the likelihood ratio framework, few open-source software solutions with a graphical user interface implementing these calculations are available for practicing forensic scientists.

Results

To address this need, we developed Lab Retriever, an open-source, freely available program that forensic scientists can use to calculate likelihood ratios for complex DNA profiles. Lab Retriever adds a graphical user interface, written primarily in JavaScript, on top of a C++ implementation of the previously published R code of Balding. We redesigned parts of the original Balding algorithm to improve computational speed. In addition to incorporating a probability of allelic drop-out and other critical parameters, Lab Retriever computes likelihood ratios for hypotheses that can include up to four unknown contributors to a mixed sample. These computations are completed nearly instantaneously on a modern PC or Mac computer.

Conclusions

Lab Retriever provides a practical software solution to forensic scientists who wish to assess the statistical weight of evidence for complex DNA profiles. Executable versions of the program are freely available for Mac OSX and Windows operating systems.

【 授权许可】

   
2015 Inman et al.

【 图 表 】

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