Anna-Katharina Lau1, Svenja Dörrer1, Chris-André Leimeister1, Christoph Bleidorn2, Burkhard Morgenstern3. 1. Universität Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, 37073 Göttingen, Germany. 2. Universität Göttingen, Department of Animal Evolution and Biodiversity, Untere Karspüle 2, Göttingen, 37073, Germany. 3. Universität Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, 37073 Göttingen, Germany. bmorgen@gwdg.de.
Abstract
BACKGROUND: In many fields of biomedical research, it is important to estimate phylogenetic distances between taxa based on low-coverage sequencing reads. Major applications are, for example, phylogeny reconstruction, species identification from small sequencing samples, or bacterial strain typing in medical diagnostics. RESULTS: We adapted our previously developed software program Filtered Spaced-Word Matches (FSWM) for alignment-free phylogeny reconstruction to take unassembled reads as input; we call this implementation Read-SpaM. CONCLUSIONS: Test runs on simulated reads from semi-artificial and real-world bacterial genomes show that our approach can estimate phylogenetic distances with high accuracy, even for large evolutionary distances and for very low sequencing coverage.
BACKGROUND: In many fields of biomedical research, it is important to estimate phylogenetic distances between taxa based on low-coverage sequencing reads. Major applications are, for example, phylogeny reconstruction, species identification from small sequencing samples, or bacterial strain typing in medical diagnostics. RESULTS: We adapted our previously developed software program Filtered Spaced-Word Matches (FSWM) for alignment-free phylogeny reconstruction to take unassembled reads as input; we call this implementation Read-SpaM. CONCLUSIONS: Test runs on simulated reads from semi-artificial and real-world bacterial genomes show that our approach can estimate phylogenetic distances with high accuracy, even for large evolutionary distances and for very low sequencing coverage.