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Metadata

Name
ATCC Even Mock Community full length 16S rRNA gene reference sequences in DADA2 format
Repository
ZENODO
Identifier
doi:10.5281/zenodo.4781067
Description
After an informative Twitter conversation about 16S sequencing bias and the importance of mock communities. I decided to&nbsp;share some of the files I had that might also help others do good microbiome analysis. The files contain&nbsp;multiple 16S rRNA sequences belonging to the 20 species reported in the ATCC even mock community and other fasta.

The ones you need for mock analysis are only the following&nbsp;two fasta files formatted for use in dada2 assignTaxonomy command (ATCC_Even_Mock_community_GTDBr202.fa&nbsp;&amp; ATCC_Even_Mock_community_RefSeq.fa). to create them I used the most recent RefSeq +RDP database on my other zenodo page (included here too) and the entire GTDB ssu collection after formatting the fasta headers (&nbsp;uploaded it here too). I have also included information I have found about the ATCC mock species and created a key to find the GTDB taxonomy.

The use case as I see it is that you can query these databases with your samples if you are using the ATCC mock community as a positive/bias control in your microbiome experiment. You can probably also use it with this awesome work by Sudarshan Shetty here https://microsud.github.io/chkMocks/articles/cExampleCustomMocks.html .

You can also do as you please with it :-). If you need me to assist or anything microbiome my email is&nbsp;alishum.ali@postgrad.curtin.edu.au

Everything I used is uploaded, happy days.&nbsp;

The primitive bash code is to help you scientists reproduce the fasta&nbsp;files.
Data or Study Types
multiple
Source Organization
Unknown
Access Conditions
available
Year
2021
Access Hyperlink
https://doi.org/10.5281/zenodo.4781067

Distributions

  • Encoding Format: HTML ; URL: https://doi.org/10.5281/zenodo.4781067
This project was funded in part by grant U24AI117966 from the NIH National Institute of Allergy and Infectious Diseases as part of the Big Data to Knowledge program. We thank all members of the bioCADDIE community for their valuable input on the overall project.