Characterizing DNA mixtures with Demixtify

Area of Science:

• Forensic science
• Genomics
• Bioinformatics

Background:

• Whole genome sequencing (WGS) is increasingly used in forensic investigations.
• Existing bioinformatics tools for WGS data analysis are often adapted from medical genomics.
• There is a significant lack of specialized software for analyzing DNA mixtures, particularly from low-quantity samples.

Purpose of the Study:

• To introduce Demixtify, a novel software tool designed for the detection and characterization of DNA mixtures from WGS data.
• To evaluate the performance of Demixtify across various population groups, sample coverages, and mixture proportions (MPs).

Main Methods:

• Genetic analyses were performed using WGS data.
• The study considered a wide spectrum of population groups, sequencing coverages, and mixture proportions.
• Demixtify was developed and tested to assess its efficacy in mixture detection and MP estimation.

Main Results:

• Demixtify demonstrates effective detection of DNA mixtures down to 0.01× coverage.
• The estimation of mixture proportions (MPs) is influenced by the source population.
• Strategic selection of genetic markers can reduce the impact of population demographics on MP estimation.

Conclusions:

• Demixtify provides a valuable solution for analyzing complex DNA mixtures in forensic WGS data.
• While MP estimation is population-sensitive, mixture detection is robust.
• Marker selection is crucial for accurate MP estimation in diverse populations.