Title |
A method for quantifying differentiation between populations at multi-allelic loci and its implications for investigating identity and paternity
|
---|---|
Published in |
Genetica, June 1995
|
DOI | 10.1007/bf01441146 |
Pubmed ID | |
Authors |
David J. Balding, Richard A. Nichols |
Abstract |
A method is proposed for allowing for the effects of population differentiation, and other factors, in forensic inference based on DNA profiles. Much current forensic practice ignores, for example, the effects of coancestry and inappropriate databases and is consequently systematically biased against defendants. Problems with the 'product rule' for forensic identification have been highlighted by several authors, but important aspects of the problems are not widely appreciated. This arises in part because the match probability has often been confused with the relative frequency of the profile. Further, the analogous problems in paternity cases have received little attention. The proposed method is derived under general assumptions about the underlying population genetic processes. Probabilities relevant to forensic inference are expressed in terms of a single parameter whose values can be chosen to reflect the specific circumstances. The method is currently used in some UK courts and has important advantages over the 'Ceiling Principle' method, which has been criticized on a number of grounds. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 9 | 4% |
United Kingdom | 6 | 2% |
Germany | 2 | <1% |
Sweden | 1 | <1% |
Malaysia | 1 | <1% |
Canada | 1 | <1% |
Brazil | 1 | <1% |
Unknown | 221 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 64 | 26% |
Researcher | 57 | 24% |
Student > Master | 24 | 10% |
Student > Doctoral Student | 17 | 7% |
Professor > Associate Professor | 13 | 5% |
Other | 44 | 18% |
Unknown | 23 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 106 | 44% |
Biochemistry, Genetics and Molecular Biology | 38 | 16% |
Computer Science | 15 | 6% |
Mathematics | 13 | 5% |
Environmental Science | 9 | 4% |
Other | 24 | 10% |
Unknown | 37 | 15% |