QIIME parameters for new subsampled Open Ref workflow

Been thinking about my choices of parameters and playing around with the new pick_open_reference_otus.py workflow.

Some Key things to remember:

  • The QIIME site reccommends running 8 parallel jobs for the m2.4xlarge Amazon AWS instances (they state this here)
  • I was on the fence about the prefiltering step but I think the 60% reference-based OTU picking will do a good job at reducing error, even for eukaryotes. So I re-enabled this command. UPDATE (8/23): I changed my mind after thinking about it more. While prefiltering is a  good idea for 16S (where you might get chloroplast DNA), I don’t think the 18S primers hit anything else that’s fishy. But I will test this out with some of the GOM data anyway.
  • The QIIME parameter file MUST contain the pick_otus:enable_rev_strand_match command (I forgot to add this in on the last run). This is vital unless you want to lose data because you fail to reverse complment! Also be careful to check the align_seqs:min_length, contingent on the dataset – e.g. I set this at 50 for the HiSeq GOM Illumina data, but upped it to 150 for the merged MiSeq 18S_chimera data. Finally, assign_taxonomy:evalue is ONLY required when you are using BLAST. If you have anything value listed here when running RDP, you’ll get an error and the taxonomy assignment won’t complete (annoying if running a workflow script…)

So the new command I ran is as follows – note I’m running at 96% this time to get a quick answer so I can look through the results:

!pick_open_reference_otus.py -i /gom_data/GOM_concat1.7_rev_demulti_1to12_2.fna -o /gom_data/uclust_openref96_ref_22Aug -r /gom_data/99_Silva_111_rep_set_euk.fasta --parallel -O 8 -s 0.1 -p /gom_data/qiime_parameters_18Sopenref_GOMamazon.txt -f

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