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MMDIT: A tool for the deconvolution and interpretation of mitochondrial DNA mixtures

NCJ Number
Forensic Science International: Genetics Volume: 55 Dated: November 2021
Sammed N. Mandapea; Utpal Smart; Jonathan L. King; Melissa Muenzler ; Kapema Bupe Kapema ; Bruce Budowle ; August E.Woerner
Date Published
November 2021

Since there are only a few software tools available for mtDNA mixture interpretation, the current project addressed this gap by developing the Mitochondrial Mixture Deconvolution and Interpretation Tool (MMDIT). 


Short tandem repeats of the nuclear genome have been the preferred markers for analyzing forensic DNA mixtures; however, when nuclear DNA in a sample is degraded or limited, mitochondrial DNA (mtDNA) markers provide a powerful alternative. Although historically considered challenging, the interpretation and analysis of mtDNA mixtures have recently received renewed interest with the advent of massively parallel sequencing. The MMDIT developed in the current project is an interactive application complete with a graphical user interface that enables users to deconvolve mtDNA (whole or partial genomes) mixtures into constituent donor haplotypes and estimate random match probabilities on these resultant haplotypes. In cases where deconvolution might not be feasible, the software enables mixture analysis directly within a binary framework (i.e., qualitatively, only using data on allele presence/absence). This article explains the functionality of MMDIT, using an example of an in vitro two-person mtDNA mixture with a ratio of 1:4. The uniqueness of MMDIT lies in its ability to resolve mixtures into complete donor haplotypes using a statistical phasing framework before mixture analysis and evaluating statistical weights employing a novel graph algorithm approach. MMDIT is the first available open-source software that can automate mtDNA mixture deconvolution and analysis. The MMDIT web application can be accessed online at https://www.unthsc.edu/mmdit/. The source code is available at https://github.com/SammedMandape/MMDIT_UI and archived on zenodo (https://doi.org/10.5281/zenodo.4770184). (publisher abstract modified)