MTaxi
MTaxi assigns mitochondrial sequencing reads to discriminate between pairs of closely related species by analyzing mtDNA transversion-type substitutions for taxonomic identification of low-coverage and ancient samples.
Key Features:
- Mitochondrial DNA Utilization: Focuses on mtDNA transversion-type substitutions to differentiate between candidate species, avoiding reliance on high-quality nuclear reference genomes.
- Read Assignment and Statistical Testing: Assigns sequencing reads to candidate species based on identified mtDNA variations and employs a binomial test to ascertain taxonomic identity.
- Efficiency at Low Coverage: Demonstrated performance at mitochondrial coverages as low as 0.5x, enabling analysis of degraded ancient samples with limited sequencing depth.
- Accuracy and Reliability: In tests with simulated ancient genomes and archaeological samples (n=18 sheep/goat and n=10 horse/donkey), achieved 100% accuracy without false positives.
Scientific Applications:
- Zooarchaeology: Distinguishes between morphologically similar taxa such as sheep and goat or horse and donkey from small bone fragments using mtDNA markers.
- Taxonomic classification of degraded samples: Enables reliable species identification from low-coverage and ancient DNA where traditional morphological or nuclear-genome-based methods are limited.
Methodology:
Detect transversion-type mtDNA substitutions between candidate species, assign sequencing reads to species based on those substitutions, and validate taxonomic identity using a binomial test.
Topics
Details
- License:
- CC-BY-4.0
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows
- Programming Languages:
- Python
- Added:
- 2/26/2023
- Last Updated:
- 11/24/2024
Operations
Publications
Atağ G, Vural KB, Kaptan D, Özkan M, Koptekin D, Sağlıcan E, Doğramacı S, Köz M, Yılmaz A, Söylev A, Togan İ, Somel M, Özer F. MTaxi : A comparative tool for taxon identification of ultra low coverage ancient genomes. Unknown Journal. 2022. doi:10.1101/2022.06.06.491147.