The University of Melbourne


Published on by Christopher Woodruff

a.  Code repository is  

     A description of the code pipeline is provided there. Item b. below describes key data files.


b.  1. Input for database generation is in   .../papercheck/workDB1, including the 

       sub-directories 16S and 23S which contain the fasta files of each strains' rRNA 

       genes. The following tarred files hold the relevant data:-




    2. Input for dataset generation is the split_zymo_hmw_r104_* files  (aa to cx)

       These have been tarred into 



       Processing of these files by extract_Seraika_16S23S_v10.R  generates the primary 

       16s and 23S datasets.


       Separately for both 16S and 23S 


    3. Input for RAD denoising is 10 fastq files. The primary datasets are in 

       .../papercheck/in   while the sub-sampled datasets are in .../papercheck

          amplicon_16S_RADfastqinput_subsampledDatasets_05022024.tar    and


       hold the sub-sampled datasets' fastq files.


    4. Input for ASV alignments, and profiling based on these, RAD outputs and the 

       reference databases.  These are held in 




       The reference databases (see i. above)  are also required, of course.


    Necessary data for running the denoising and profiling consists of 


       i.    workDB1_16S_23S_blastn_databases.tar

      ii.    amplicon_D6322_16S_trimmed_05022024.fastq

     iii.    amplicon_D6322_23S_trimmed_05022024.fastq


      iv.    amplicon_16S_RADfastqinput_subsampledDatasets_05022024.tar

       v.    amplicon_23S_RADfastqinput_subsampledDatasets_05022024.tar


      vi.    denoised_amplicon_D6322_16S23S_05022024_10datasets_ASVs_fasta.tar

     vii.    amplicon_16S_RADfastqoutput_05022024.tar

    viii.    amplicon_23S_RADfastqoutput_05022024.tar

      ix.    RAD_amplicon_16S23S_05022024_10datasets_text_output_06022024.tar


    Items i. to iii. allow RAD denoising of the primary 16S and 23S datasets.

    Items iv. and v., together with item i. allow RAD denoising of the sub-sampled 


    Items vi., vii., viii. and ix. allow identification and quantification of the sample 

             microbiota for all datasets.




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