Internal validation of STRmix™ for the interpretation of single source and mixed DNA profiles

2017 ◽  
Vol 29 ◽  
pp. 126-144 ◽  
Author(s):  
Tamyra R. Moretti ◽  
Rebecca S. Just ◽  
Susannah C. Kehl ◽  
Leah E. Willis ◽  
John S. Buckleton ◽  
...  
2004 ◽  
Vol 49 (3) ◽  
pp. 1-8 ◽  
Author(s):  
John H. Ryan ◽  
Jeffrey K. Barrus ◽  
Bruce Budowle ◽  
Cynthia M. Shannon ◽  
Victor W. Thompson ◽  
...  

2021 ◽  
Author(s):  
Kaitlin Huffman ◽  
Erin Hanson ◽  
Jack Ballantyne

DNA mixtures are a common source of crime scene evidence and are often one of the more difficult sources of biological evidence to interpret. With the implementation of probabilistic genotyping (PG), mixture analysis has been revolutionized allowing previously unresolvable mixed profiles to be analyzed and probative genotype information from contributors to be recovered. However, due to allele overlap, artifacts, or low-level minor contributors, genotype information loss inevitably occurs. In order to reduce the potential loss of significant DNA information from donors in complex mixtures, an alternative approach is to physically separate individual cells from mixtures prior to performing DNA typing thus obtaining single source profiles from contributors. In the present work, a simplified micro-manipulation technique combined with enhanced single-cell DNA typing was used to collect one or few cells, referred to as direct single-cell subsampling (DSCS). Using this approach, single and 2-cell subsamples were collected from 2-6 person mixtures. Single-cell subsamples resulted in single source DNA profiles while the 2-cell subsamples returned either single source DNA profiles or new mini-mixtures that are less complex than the original mixture due to the presence of fewer contributors. PG (STRmixTM) was implemented, after appropriate validation, to analyze the original bulk mixtures, single source cell subsamples, and the 2-cell mini mixture subsamples from the original 2-6-person mixtures. PG further allowed replicate analysis to be employed which, in many instances, resulted in a significant gain of genotype information such that the returned donor likelihood ratios (LRs) were comparable to that seen in their single source reference profiles (i.e., the reciprocal of their random match probabilities). In every mixture, the DSCS approach gave improved results for each donor compared to standard bulk mixture analysis. With the 5- and 6- person complex mixtures, DSCS recovered highly probative LRs (> 1020) from donors that had returned non-probative LRs (<103) by standard methods.


2020 ◽  
Vol 44 ◽  
pp. 102192 ◽  
Author(s):  
Sarah Riman ◽  
Hari Iyer ◽  
Lisa A. Borsuk ◽  
Peter M. Vallone
Keyword(s):  

2013 ◽  
Vol 7 (5) ◽  
pp. 516-528 ◽  
Author(s):  
Duncan Taylor ◽  
Jo-Anne Bright ◽  
John Buckleton
Keyword(s):  

2006 ◽  
Vol 175 (4S) ◽  
pp. 402-402
Author(s):  
Alberto Briganti ◽  
K.-H. Felix Chun ◽  
Shahrokh F. Shariat ◽  
Yair Lotan ◽  
Ganesh S. Palapattu ◽  
...  

2001 ◽  
Vol 11 (PR3) ◽  
pp. Pr3-577-Pr3-584 ◽  
Author(s):  
A. Devi ◽  
H. Parala ◽  
W. Rogge ◽  
A. Wohlfart ◽  
A. Birkner ◽  
...  

2019 ◽  
Author(s):  
Torsten Diekhoff ◽  
Michael Fuchs ◽  
Nils Engelhard ◽  
Kay-Geert Hermann ◽  
Michael Putzier ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document