schmutzi

schmutzi estimates present-day human contamination and reconstructs endogenous mitochondrial genomes from ancient DNA (aDNA) samples to enable accurate mitochondrial sequence analysis despite degradation and contamination.

Key Features:

• Iterative joint estimation: Iteratively estimates present-day human contamination while reconstructing the endogenous mitochondrial genome from the same dataset.
• Deamination-aware modeling: Exploits cytosine deamination patterns to distinguish endogenous aDNA molecules from modern contaminant sequences.
• Fragment length analysis: Uses fragment length distributions as an additional signal to discriminate endogenous fragments from contamination.
• High-contamination resilience: Can accurately reconstruct endogenous mitochondrial genomes even when contamination exceeds 50%.
• Coverage-dependent contamination estimates: Produces contamination estimates whose reliability improves with increased sequencing coverage.

Scientific Applications:

• Paleogenomics: Recovery and authentication of mitochondrial genomes from ancient and degraded samples.
• Archaeology: Genetic characterization of archaeological human remains in the presence of modern contamination.
• Evolutionary biology: Inference of historical population mitochondrial lineages and assessment of contamination in evolutionary studies.

Methodology:

Uses an iterative algorithm that jointly estimates present-day human contamination and reconstructs the endogenous mitochondrial genome by modeling cytosine deamination patterns and fragment length distributions, with sequencing coverage informing estimate reliability.