Classifier for the SNP-Based Inference of Ancestry

• NCJ Number: 201547
• Journal: Journal of Forensic Sciences Volume: 48 Issue: 4 Dated: July 2003 Pages: 771-782
• Author(s): Tony Frudakis Ph.D.; Venkateswarlu K Ph.D.; Matthew J. Thomas Ph.D.; Zach Gaskin B.S.; Siva Ginjupalli M.S.; Sitarama Gunturi Ph.D.; Viswanathan Ponnuswamy M.S.; Sivamiani Natarajan Ph.D.; Ponnuswamy Kolathupalayam Nachimuthu Ph.D.
• Date Published: July 2003
• Length: 12 pages
• Publication Format: Article
• Publication Type: Report (Study/Research)
• Language: English
• Country: United States of America

Annotation

This study identified biallelic markers that can be used to ascertain ancestral affiliation from DNA samples.

Abstract

The ability to offer reliable and accurate ancestral identification from DNA specimens would be of valuable use. Such information could guide investigators in criminal cases by narrowing the field of potential suspects. However, current STR methods for inference of ancestral identification from DNA have technical and methodological limitations. In an effort to identify biallelic markers useful in the inference of ancestral identification, the authors screened 211 SNP’s in the human pigmentation and xenobiotic metabolism genes. Results revealed differences in the allele frequencies of 56 SNP’s between groups of unrelated Asians, Africans, and Europeans. Both the observed and simulated log likelihood ratios suggested the markers to be of significant value for detecting ancestral affiliation. The log likelihood ratios were among the best of the STR batteries described. The authors describe their linear classification model for incorporating the SNP’s into a classifier model with 99 percent, 98 percent, and 100 accuracy levels for identifying individuals with varying ancestral descent. The next step is the development of a practical multiplex test for the inference of ancestral heritage in a forensic setting. Tables, references, appendix