Projects per year
MOTIVATION: Despite recent advancements in sequencing technologies and assembly methods, obtaining high-quality microbial genomes from metagenomic samples is still not a trivial task. Current metagenomic binners do not take full advantage of assembly graphs and are not optimized for long-read assemblies. Deep graph learning algorithms have been proposed in other fields to deal with complex graph data structures. The graph structure generated during the assembly process could be integrated with contig features to obtain better bins with deep learning.
RESULTS: We propose GraphMB, which uses graph neural networks to incorporate the assembly graph into the binning process. We test GraphMB on long-read datasets of different complexities, and compare the performance with other binners in terms of the number of High Quality (HQ) genome bins obtained. With our approach, we were able to obtain unique bins on all real datasets, and obtain more bins on most datasets. In particular, we obtained on average 17.5% more HQ bins when compared with state-of-the-art binners and 13.7% when aggregating the results of our binner with the others. These results indicate that a deep learning model can integrate contig-specific and graph-structure information to improve metagenomic binning.
AVAILABILITY AND IMPLEMENTATION: GraphMB is available from https://github.com/MicrobialDarkMatter/GraphMB.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
|Number of pages||7|
|Publication status||Published - Oct 2022|
Bibliographical note© The Author(s) 2022. Published by Oxford University Press.
- Genome, Microbial
- Sequence Analysis, DNA/methods
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- 3 Active
Data Science meets Microbial Dark Matter
Albertsen, M., Hose, K., Nielsen, T. D., Lamurias, A. & Mølvang Dall, S.
Villum Fonden, Danish E-infrastructure Cooperation
01/01/2021 → 31/12/2023
Poul Due Jensen Professorate in Big Data and Artificial Intelligence
Hose, K., Jendal, T. E. & Hansen, E. R.
01/11/2019 → 31/10/2024
Microflora Danica: The Microbiome of Denmark
Albertsen, M., Nielsen, P. H., Jensen, T. B. N., Sørensen, E. A., Sereika, M., Dottorini, G., Petriglieri, F., Jørgensen, V. R., Kirkegaard, R. H., Yang, Y., Karst, S. M., Giguere, A. T., Knutsson, S., Singleton, C. M., Dueholm, M. K. D. & Mølvang Dall, S.
01/01/2019 → 31/12/2025