DBLR™

Application designed for the rapid calculation of likelihood ratios (LRs) using STRmix™ deconvolutions.

Database (DB) likelihood ratios (LR) play an integral role in DNA analysis and identification. In order to correctly determine the match statistic when studying a sample, forensic analysts need a tool that provides them with reliable information – at a fast pace.

DBLR™, developed by the Institute of Environmental Science and Research (ESR), is an application specifically designed to calculate millions of LRs – in a matter of seconds. Through this application, forensic analysts can identify expected ranges from different hypotheses – and can determine if the sample is suitable for comparison.

In order to calculate LRs efficiently and effectively, DBLR™ is used in conjunction with STRmix™, an innovative forensic software tool also developed by ESR. DBLR™ conducts rapid calculation of LRs using STRmix™ deconvolutions. Watch a short video introducing DBLR!

DBLR™ performs the following functions:

Visualizes the value of DNA mixture evidence by calculating expected LRs for true and non-contributors using randomly generated individuals
Achieves quick database searches
Undertakes mixture-to-mixture matches
Calculates any kinship relationship conceivable (including modelling of linkage, mutation and F_ST)
Assigns Kinship LRs for single source NGS profiles
Manages automated searches for one or many DNA profiles against one or many databases of known individuals. Now includes direct matching between databases
Calculates thousands of LRs and plots them into a comprehensive diagram
Carries out familial searching for a range of different relationships
Conducts automated searches for one or multiple DNA profiles against databases of known individuals
Determines the profiles of the most likely contributors
Directly compares one or many components of a forensic mixture to a database of known individuals
Runs on users’ PCs without high-speed computing
Searches for common distributors between mixed DNA profiles
Uses databases of known contributors and STRmix™ deconvolutions for matching purposes
Works with efficient algorithms to generate fast calculations of LRs