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Code and documentation are available at http://segatalab.cibio.unitn.it/tools/viromeqc.
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This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 716575) to N.S. The work was also supported by MIUR ‘Futuro in Ricerca’’ RBFR13EWWI_001 and by the European Union (H2020-SFS-2018-1 project MASTER-818368 and H2020-SC1-BHC project ONCOBIOME-825410) to N.S.
The authors declare no competing interests.
Supplementary Methods, Supplementary Note 1 and Supplementary Figures 1–7
Summary of the 2,050 virome datasets considered in the analysis. Dataset sample sizes are related to the actual number of samples that could be classified as DNA VLP viromes according to the available metadata. The reference number refers to Fig. 1. Fig. 2d and Supplementary Fig. 1.
Summary of the 2,189 metagenomes and 109 synthetic metagenomes and mock communities considered in the analysis. Dataset sample sizes are related to the actual number of samples that could be classified as DNA metagenomes according to the available metadata. The reference number refers to Fig. 1. Fig. 2d and Supplementary Fig. 1.
Full dataset of metagenomes and viromes. Contaminant abundances and enrichment data for all the 1,871 metagenomes, 1,670 viromes and 109 synthetic and mock communities that passed all quality controls. Sample type and number of starting reads are provided, as well as the percentage of SSU and LSU rRNAs stratified by life domain.
Validation of the rRNA mapping approach. Expected abundances of 16S rRNA genes are reported for the 108 synthetic and mock communities (tab 1) and 917 16S amplicon sequencing samples (tab 2). Control metagenomes and 16S samples were mapped against the SSU rRNA genes and filtered at different stringency thresholds (see Supplementary Methods). For the amplicon 16S samples at the expected value was set to 100%. The selected threshold is highlighted in blue. The composition of each synthetic metagenome is reported in tab 3. The rRNA abundances in RNA viromes are reported in tab 4.
Detection of single-copy bacterial markers in viral genomes. Number of genomes in each database in which the 31 single-copy markers are detected. The IMG/VR database was split into isolate viruses and uncultivated viruses (tab 1). Number of distinct single-copy markers detected in each database (tab 2).
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Zolfo, M., Pinto, F., Asnicar, F. et al. Detecting contamination in viromes using ViromeQC. Nat Biotechnol 37, 1408–1412 (2019). https://doi.org/10.1038/s41587-019-0334-5
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