Published December 14, 2022
| Version 1
Dataset
Open
Investigation of machine learning algorithms for taxonomic classification of marine metagenomes
Description
Training, testing, and blind datasets used for machine learning algorithms for taxonomic classification of marine metagenomes:
- K12.kmers.txt - 12bp k-mer vocabulary constructed by Jellyfish v1.1.11 from 47,894 genomes in GTDB release 202
- MarRef_1.6.tsv - Metadata file downloaded from MarRef v1.6
- MarRef.genustrain.fasta - Training set from MarRef v1.6 (seed=808) used for genus classification
- MarRef.genustest.fasta - Testing set from MarRef v1.6 (seed=747) used for genus classification
- MarRef.speciestrain.fasta - Training set from MarRef v1.6 (seed=808) used for species classification
- MarRef.speciestest.fasta - Testing set from MarRef v1.6 (seed=747) used for species classification
- MarRef.traintest.key.tsv - Table containing MarRef accession, GenBank accession, GenBank taxonomy ID, taxonomic information, and labels used for species and genus testing and training
- anonymous_reads_*.fq - Blind datasets (1-10) in interleaved fastq format
- reads_mapping_*.tsv - Key for blind datasets 1-10. Each sequence header is mapped to its corresponding MarRef accession and NCBI taxonomic ID.
Files
K12.kmers.txt
Files
(33.6 GB)
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