A New Computational Deconvolution Algorithm for the Analysis of Forensic DNA Mixtures with SNP Markers.

ABSTRACT: Single nucleotide polymorphisms (SNPs) support robust analysis on degraded DNA samples. However, the development of a systematic method to interpret the profiles derived from the mixtures is less studied, and it remains a challenge due to the bi-allelic nature of SNP markers. To improve the discriminating power of SNPs, this study explored bioinformatic strategies to analyze mixtures. Then, computer-generated mixtures were produced using real-world massively parallel sequencing (MPS) data from the single samples processed with the Precision ID Identity Panel. Moreover, the values of the frequency of major allele reads (F_MAR) were calculated and applied as key parameters to deconvolve the two-person mixtures and estimate mixture ratios. Four custom R language scripts (thre

SUBMITTER: Yin Y 

PROVIDER: S-EPMC9141285 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature