Date of Award
Spring 5-2018
Document Type
Thesis
Degree Name
Master of Science (MS)
Department/Program
Forensic Science
Language
English
First Advisor or Mentor
Mechthild Prinz
Second Reader
Lawrence Kobilinsky
Third Advisor
Elisa Wurmbach
Abstract
This study examined and analyzed 266 samples using ForenSeqTM Signature Prep Kit B. Samples from various populations such as African American, East Asian, South Asian, European, and Mixed population were included in the study. Primer Mix B targets 27 autosomal STRs (aSTRs), 24 Y-STRs, 7 X-STRs, and 94 identity Single Nucleotide Polymorphisms (iSNPs), 24 phenotypic SNPs (pSNPs), and 56 ancestry SNPs (aSNPs), coming to a total of 231 targets. The study mainly focused on the quality of data generated by the instrument as well as for the accuracy of eye and hair color as well as biogeographical ancestry predictions performed by the UAS software. After obtaining the genotypes from UAS (Universal Analysis Software), outcomes were compared to predictions performed by various algorithms available online for eye and hair color as well as biogeographical ancestry such as 8-plex, Erasmus Medical Center and the Forensic Resource/Reference on Genetics-knowledge base (FROG-kg).
Throughout 9 experimental runs, dropouts were observed for several specific SNPs indicating low quality which resulted in a low prediction rate for eye and hair color. No errors in eye and hair color estimations were observed for the populations like African American, East Asian, and South Asian, but all available algorithms had difficulties in the prediction of the intermediate eye color by all available algorithms. However, the 8-plex system had a higher intermediate eye color estimation rate. Biogeographical ancestry estimation by UAS had lower error rates compared to the FROG-kb but was unable to predict the South Asian population.
Recommended Citation
Jani, Krupa Vijaykumar, "Evaluation of Illumina’s ForenSeqTM Signature Prep Kit for Eye and Hair Color as well as Biogeographical Ancestry Predictions" (2018). CUNY Academic Works.
https://academicworks.cuny.edu/jj_etds/83
