NIST will host a series of free webinars focused on topics of interest to DNA analysts. This four-hour webinar will be held on May 28, 2014, from 1:00 pm – 5:00 pm (EDT), and will focus on probabilistic genotyping for complex low-level DNA mixtures.
Watch a recording of the webinar on this page.
Download the agenda (PDF).
Speaker presentation slides (links open PDFs)
Charlotte Word's slides
Ate Kloosterman's slides (quality issues at NFI)
Michael Coble (overview)
Ate Kloosteman (LRmix)
Michael Coble (conclusion)
Recent improvements in both STR chemistry and CE instrumentation have exacerbated interpretation as laboratories try to analyze highly complex mixtures such as "touch" items with (a) more than two contributors and/or (b) low-level contributors with possible dropout. Current strategies to evaluate low-level mixtures with dropout using the binary Likelihood Ratio (LR) are insufficient and may overstate the weight of the evidence.
Recently, the ISFG published recommendations for the interpretation of low-level mixtures when dropout is possible (Gill et al. 2012). Software programs are now available that utilize a "semi-continuous" approach, incorporating a probability of dropout in the LR; or a "continuous" model of interpretation which incorporates the biological variation within the data.
To provide an understanding of the benefits of probabilistic genotyping for complex low-level DNA mixtures.
Attendees will be provided an overview of the two approaches to probabilistic genotyping for complex mixtures. Four invited speakers with casework experience will share their ideas on why their laboratory considered the need for probabilistic genotyping software.
The workshop is intended for anyone interested in probabilistic genotyping software packages to aid in the evaluation of mixed DNA profiles, including DNA analysts, DNA technical leaders, laboratory directors, attorneys and consultants. The presentations will be aimed toward an audience with experience in DNA profile interpretation, statistical calculations and population genetics.