The Use of Forensic DNA Phenotyping in Predicting Appearance and Biogeographic Ancestry.

The Use of Forensic DNA Phenotyping in Predicting Appearance and Biogeographic Ancestry.

Schneider, Peter M;Prainsack, Barbara;Kayser, Manfred;
deutsches arzteblatt international 2019 Vol. 51-52 pp. 873-880
227
schneider2019thedeutsches

Abstract

Persons whose identifying DNA profile (STR profile) is not yet known to the ingvestigating authorities cannot be identified by standard forensic DNA analysis (STR profiling) as it is now practiced. In view of the current public debate, particularly in Germany, on the legalization of so-called forensic DNA phenotyping, we present its scientific basis, societal aspects, and forensic applications and describe the analytic techniques that are now available.This review is based on pertinent publications that were retrieved by a selective search in PubMed and in public media, and on the authors' own research.Forensically validated DNA test systems are available for the categorization of eye, hair, and skin color and the inference of continental biogeographic ancestry. As for statistical measures of test accuracy, the AUC (area under the curve) values lie in the range 0.74-0.99 for eye color, 0.64-0.94 for hair color, and 0.72-0.99 for skin color, depending on the predictive model and color category used.The corre- sponding positive predictive values (PPV) are lower. Empirical social-scientific research on forensic DNA phenotyping has shown that preserving privacy and protecting against discrimination are major ethical and regulatory considerations.All three methods of forensic DNA phenotyping-the predition of exter- nally visible characteristics, biogeographic ancestry, and the estimation of age from crime scene DNA-require a proper regulatory framework and should be used in conjunction with each other. Before forensic DNA phenotyping can be implemented in forensic practice, steps must be taken to minimize the risks of violation of privacy scrimination and to ensure that these methods are used transpar- ently and proportionately.

Citation

ID: 90013
Ref Key: schneider2019thedeutsches
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
90013
Unique Identifier:
10.3238/arztebl.2019.0873
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet