Literature DB >> 30132900

The Probabilistic Genotyping Software STRmix: Utility and Evidence for its Validity.

John S Buckleton1,2, Jo-Anne Bright1, Simone Gittelson3, Tamyra R Moretti4, Anthony J Onorato4, Frederick R Bieber5, Bruce Budowle6, Duncan A Taylor7,8.   

Abstract

Forensic DNA interpretation is transitioning from manual interpretation based usually on binary decision-making toward computer-based systems that model the probability of the profile given different explanations for it, termed probabilistic genotyping (PG). Decision-making by laboratories to implement probability-based interpretation should be based on scientific principles for validity and information that supports its utility, such as criteria to support admissibility. The principles behind STRmix™ are outlined in this study and include standard mathematics and modeling of peak heights and variability in those heights. All PG methods generate a likelihood ratio (LR) and require the formulation of propositions. Principles underpinning formulations of propositions include the identification of reasonably assumed contributors. Substantial data have been produced that support precision, error rate, and reliability of PG, and in particular, STRmix™. A current issue is access to the code and quality processes used while coding. There are substantial data that describe the performance, strengths, and limitations of STRmix™, one of the available PG software.
© 2018 American Academy of Forensic Sciences.

Entities:  

Keywords:  zzm321990DNAzzm321990; STRmix™; forensic science; probabilistic genotyping; validation

Mesh:

Year:  2018        PMID: 30132900     DOI: 10.1111/1556-4029.13898

Source DB:  PubMed          Journal:  J Forensic Sci        ISSN: 0022-1198            Impact factor:   1.832


  9 in total

1.  Typing of semen-containing mixtures using ARMS-based semen-specific CpG-InDel/STR markers.

Authors:  Zeqin Li; Yidan Li; Na Liu; Fang Yuan; Feng Liu; Jinding Liu; Keming Yun; Jiangwei Yan; Gengqian Zhang
Journal:  Int J Legal Med       Date:  2022-05-28       Impact factor: 2.686

2.  MaSTR™: an effective probabilistic genotyping tool for interpretation of STR mixtures associated with differentially degraded DNA.

Authors:  Mitchell M Holland; Teresa M Tiedge; Abigail J Bender; Sidney A Gaston-Sanchez; Jennifer A McElhoe
Journal:  Int J Legal Med       Date:  2022-01-29       Impact factor: 2.686

3.  Open practices in our science and our courtrooms.

Authors:  Michael D Edge; Jeanna Neefe Matthews
Journal:  Trends Genet       Date:  2021-11-02       Impact factor: 11.821

4.  A novel approach for rapid cell assessment to estimate DNA recovery from human bone tissue.

Authors:  Thien Ngoc Le; Oliva Handt; Julianne Henry; Adrian Linacre
Journal:  Forensic Sci Med Pathol       Date:  2021-10-11       Impact factor: 2.456

Review 5.  Interpol review of forensic biology and forensic DNA typing 2016-2019.

Authors:  John M Butler; Sheila Willis
Journal:  Forensic Sci Int       Date:  2020-02-20       Impact factor: 2.395

6.  The population genetics characteristics of a 90 locus panel of microhaplotypes.

Authors:  Andrew J Pakstis; Neeru Gandotra; William C Speed; Michael Murtha; Curt Scharfe; Kenneth K Kidd
Journal:  Hum Genet       Date:  2021-10-13       Impact factor: 4.132

Review 7.  A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™.

Authors:  Peter Gill; Corina Benschop; John Buckleton; Øyvind Bleka; Duncan Taylor
Journal:  Genes (Basel)       Date:  2021-09-30       Impact factor: 4.096

8.  Internal Validation of MaSTR™ Probabilistic Genotyping Software for the Interpretation of 2-5 Person Mixed DNA Profiles.

Authors:  Michael S Adamowicz; Taylor N Rambo; Jennifer L Clarke
Journal:  Genes (Basel)       Date:  2022-08-11       Impact factor: 4.141

9.  Probabilistic Genotyping of Single Cell Replicates from Mixtures Involving First-Degree Relatives Prevents the False Inclusions of Non-Donor Relatives.

Authors:  Kaitlin Huffman; Jack Ballantyne
Journal:  Genes (Basel)       Date:  2022-09-15       Impact factor: 4.141

  9 in total

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