Hello,
It is my understanding that in QIIME 1.9.1 you were able to use the following commands to 1) remove singletons and 2) filter out anything with a relative abundance below a certain percentage:
-
filter_otus_from_otu_table.py -i otu_table.biom -o otu_table_no_singletons.biom -n 2
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filter_otus_from_otu_table.py -i table.biom -o table_no_low_abundances.biom --min_count_fraction 0.00005
From what I understand, DADA2 should take care of my issue 1), correct? If I’m right in assuming so, how does DADA2 ensure that singletons are removed or is there some other parameter I need to be adding to make sure that is done?
For the low abundances, based on Bokulich (2013): Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing we’d like ensure anything with a relative abundance <0.005% is removed before doing our alpha and beta diversity analyses. I’ve seen that “–p-min-frequency” can be used with “qiime feature-table filter-features” to remove low abundance features from a table. However, I am trying to find a way to do something similar to what was done with the 2013 paper and remove anything at <0.005% after obtaining the relative abundances as follows:
qiime taxa collapse
–i-table table.qza
–i-taxonomy taxonomy.qza
–p-level 6
–o-collapsed-table genus-table.qza
qiime feature-table relative-frequency
–i-table genus-table.qza
–o-relative-frequency-table rel-genus-table.qza
qiime tools export rel-genus-table.qza
–output-dir RelativeAbundanceTables/Genus
cd RelativeAbundanceTables/Genus
biom convert -i feature-table.biom -o rel-genus-table.tsv --to-tsv
Is there a way to do this? If not, I’m not really sure how to equate that 0.005% for --p-min-frequency in the FeatureTable step.
Thanks in advance!