we have an OTU table!

Goal: get an OTU table using denoised data

Methods:
On our cluster, with qiime 1.6.0:
pick_otus.py -i combined_denoised_seqs.fna -z -r /share/apps/qiime_software/gg_otus-12_10-release/rep_set/97_otus.fasta -m uclust_ref --uclust_otu_id_prefix qiime_otu -o uclust_ref_gg12_

then
pick_rep_set.py -i uclust_ref_gg12_/combined_denoised_seqs_otus.txt -f combined_denoised_seqs.fna -r /share/apps/qiime_software/gg_otus-12_10-release/rep_set/97_otus.fasta -o pick_rep_set

On EC2 running qiime 1.7.0:
parallel_assign_taxonomy_rdp.py -i /home/ubuntu/data/soil/pick_rep_set.fasta -O 8 --rdp_max_memory 4000 -o /home/ubuntu/data/soil/tax_assign_out2

Back on our cluster with qiime 1.6.0:
make_otu_table.py -i combined_denoised_seqs_otus.txt -t pick_rep_set_tax_assignments.txt -o soil_otu_table.biom

Result: We have an OTU table called soil_otu_table.biom! More info about it:
Num samples: 61
Num otus: 12528
Num observations (sequences): 646884.0
Table density (fraction of non-zero values): 0.1284

Seqs/sample summary:
Min: 3279.0
Max: 33718.0
Median: 9823.0
Mean: 10604.6557377
Std. dev.: 5310.3842468
Median Absolute Deviation: 3709.0
Default even sampling depth in
core_qiime_analyses.py (just a suggestion): 3279.0
Sample Metadata Categories: None provided
Observation Metadata Categories: taxonomy