VirHunter: a deep learning-based method for detection of novel RNA viruses in plant sequencing data
Description
This storage contains 2 archives: toy datasets to test the training of the VirHunter and weights of the fully trained VirHunter models for 3 host species (peach, grapevine, sugar beet) and for fragment sizes 500 and 1000. . The toy dataset consists of 3 archived files: 'viruses.fasta', 'host.fasta', 'bacteria.fasta'. 'viruses.fasta' contains 10000 randomly selected plant viruses from the virus dataset described in the paper. 'host.fasta' consists of peach chromosome 2. 'bacteria.fasta' consists of 10 bacterial genomes selected randomly: GCF_000284415, GCF_000590555, GCF_001548055, GCF_002795265, GCF_003330825, GCF_003957805, GCF_005845345, GCF_009176625, GCF_010748935, GCF_014681765
Resources
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http://data.europa.eu/88u/dataset/oai-zenodo-org-5957275 |
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http://data.europa.eu/88u/dataset/oai-zenodo-org-5957275 |
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http://data.europa.eu/88u/dataset/oai-zenodo-org-5957275 |
Tags
- plant-virome
- deep-learning
- novel-virus-detection
- alignment-free-method