Processing Questions (visualizations and taxonomy assignment)

Thank you @gregcaporaso! It worked nicely.

I have a couple of follow-up questions:

1 ) About Emperor:

I am trying to get a biplot of unifrac / weighted unifrac distances. When I pass qiime emperor plot --help I cannot see any option that mentions biplots, like I see in the make_emperor.py.

Can I get biplots on QIIME2? Or should I transfer to QIIME1?

In case I need to transfer back, how would I get the matrices with the taxonomy data added to them?

  1. Taxonomy assignment:

I need to get to a feature table that would give me the relative abundances of each feature, per sample. If I understand correctly, this would be kind of like a junction of the output of

qiime taxa tabulate --i-data taxonomy.qza

and

qiime dada2 denoise --i-demultiplexed-seqs

Is there a way of getting to this?

Basically I would want the raw data to get the taxa barplots, so I can merge low relative abundance taxa into a single cluster and make a simpler barplot on my own.

Thank you very much, and sorry for all the questions!

I am trying to get a biplot of unifrac / weighted unifrac distances. When I pass qiime emperor plot --help I cannot see any option that mentions biplots, like I see in the make_emperor.py.

Can I get biplots on QIIME2? Or should I transfer to QIIME1?

The q2-emperor plugin in QIIME 2 doesn’t currently support biplots. I created an issue here to track progress on that. For now, I recommend using QIIME 1 (make_emperor.py) to create biplots.

In case I need to transfer back, how would I get the matrices with the taxonomy data added to them?

There’s a few steps to exporting your QIIME 2 data in order to create biplots in QIIME 1:

  1. Use qiime taxa collapse to create a taxonomy table at a specific level (--p-level) from an unrarefied feature table (--i-table) and taxonomy feature data (--i-taxonomy). The unrarefied feature table will be a .qza file with type FeatureTable[Frequency] and the taxonomy feature data will be a .qza file with type FeatureData[Taxonomy].

  2. Convert the taxonomy table from step 1 into relative abundances with qiime feature-table relative-frequency.

  3. Use qiime tools export to export the relative abundance taxonomy table in BIOM format.

  4. Use biom convert to convert the exported BIOM file into TSV format (see this tutorial).

  5. Export your PCoA coordinates (they’ll be stored in a .qza of type PCoAResults) using qiime tools export.

  6. Use make_emperor.py with the TSV taxa table and the exported PCoA results from step 5.

That’s a lot of steps! We’ll be simplifying this in the future so that you can create biplots directly in QIIME 2. Let us know if you have any questions along the way.

I need to get to a feature table that would give me the relative abundances of each feature, per sample. If I understand correctly, this would be kind of like a junction of the output of

qiime taxa tabulate --i-data taxonomy.qza

and

qiime dada2 denoise --i-demultiplexed-seqs

Is there a way of getting to this?

To get a feature table of relative abundances, use qiime feature-table relative-frequency to convert your .qza of type FeatureTable[Frequency] into a .qza of type FeatureTable[RelativeFrequency]. If you’re following along with the QIIME 2 tutorials, you should be able to use the feature table created by qiime dada2 denoise as input to qiime feature-table relative-frequency.

Basically I would want the raw data to get the taxa barplots, so I can merge low relative abundance taxa into a single cluster and make a simpler barplot on my own.

You can use qiime taxa collapse to create a taxonomy table from a feature table, then qiime feature-table relative-frequency to convert the taxonomy table into relative frequencies, and qiime tools export to export the raw data in BIOM format. biom convert can be used to convert the file into TSV (if that’s what you’re looking for).

Let us know if you have any further questions!