DADA2 formatted 16S rRNA gene sequences for both bacteria & archaea
Contributors
Contact person:
Data curator:
Other:
Researcher:
- 1. Trend Laboratory, Curtin University of Technology
- 2. Commonwealth Scientific and Industrial Research Organisation (CSIRO)
- 3. WA Human Microbiome Collaboration Centre (WAHMCC), Trend Laboratory, Curtin University
Description
These two combined bacterial and archaeal 16S rRNA gene sequence databases were collated from various sources and formatted for the purpose of using the "assignTaxonomy" command within the DADA2 pipeline.
- RefSeq+RDP: This database contains 14676 bacterial & 660 archaea full 16S rRNA gene sequences. It was compiled in 14/05/2018 from predominantly the NCBI RefSeq 16S rrna database (https://www.ncbi.nlm.nih.gov/refseq/targetedloci/16S_process/) and was supplemented with extra sequences from the RDP database (https://rdp.cme.msu.edu/misc/resources.jsp).
- Genome Taxonomy Database (GTDB): our dada2 formatted GTDB reference sequence set contains 20486 bacteria and 1073 archaea full 16S rRNA gene sequences. The database was downloaded from (http://gtdb.ecogenomic.org/downloads) on 20/11/2018.
The formatting to DADA2 format of the databases was done using a locally written python 2.7 script. The script takes as input a taxonomy .txt file and a fasta file as provided by the core databases creators and then these two files are matched according to a unique sequence identifier available in both files. Then it outputs a fasta file with all 7 taxonomy ranks separated by ";" as required for DADA2 compatibility. Additionally, we have concatenated the unique sequence ID be it NCBI/RDP or GTDB ID to the species entry. We see this as an important QC step to highlight the issues/confidence associated with short read taxonomy assignment at the more finer rank levels.
Notes
Files
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Additional details
References
- Parks, D. H., et al. (2018). "A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life." Nature Biotechnology.
- Cole, J. R., Q. Wang, J. A. Fish, B. Chai, D. M. McGarrell, Y. Sun, C. T. Brown, A. Porras-Alfaro, C. R. Kuske, and J. M. Tiedje. 2014. Ribosomal Database Project: data and tools for high throughput rRNA analysis Nucl. Acids Res. 42(Database issue):D633-D642; doi: 10.1093/nar/gkt1244 [PMID: 24288368]
- NCBI 16S RefSeq Nucleotide sequence records: https://www.ncbi.nlm.nih.gov/nuccore?term=33175%5BBioProject%5D+OR+33317%5BBioProject%5D