Only show genus taxonomy on ancombc graphic?

[Liviacmg]

Hi @colinvwood ,

I tried to use the qiimefeature-table filter-seqs, by using the metadata like this:

qiime feature-table filter-seqs
--i-data rep-seqs.qza
--m-metadata-file metadado-validado.tsv
--p-where "[Host_disease]='BipolarDisorder'"
--o-filtered-data bipolar-rep-seqs.qza

But then were this error:

Plugin error from feature-table:

All features were filtered out of the data.

Debug info has been saved to /tmp/qiime2-q2cli-err-jceyjop0.log

Traceback (most recent call last):
File "/usr/local/miniconda3/envs/qiime2-2023.5/lib/python3.8/site-packages/q2cli/commands.py", line 468, in call
results = action(**arguments)
File "", line 2, in filter_seqs
File "/usr/local/miniconda3/envs/qiime2-2023.5/lib/python3.8/site-packages/qiime2/sdk/action.py", line 274, in bound_callable
outputs = self.callable_executor(
File "/usr/local/miniconda3/envs/qiime2-2023.5/lib/python3.8/site-packages/qiime2/sdk/action.py", line 509, in callable_executor
output_views = self._callable(**view_args)
File "/usr/local/miniconda3/envs/qiime2-2023.5/lib/python3.8/site-packages/q2_feature_table/_filter.py", line 118, in filter_seqs
raise ValueError('All features were filtered out of the data.')
ValueError: All features were filtered out of the data.

And then I saw that in this post there is exactly the same problem as I am facing:

Error with feature-table filter-seqs: All features were filtered out of the data.

At second glance, @Ricardo_Ramiro, it looks like you have an ID mismatch here - your command is trying to filter the features in your rep-seqs using the sample ids from your metadata file. Your sample and feature IDs are different, so the query finds no matches. Try using your --p-where query to filter samples from your FeatureTable[Frequency]. Filtering out the samples that match your query will produce a FeatureTable[frequency] file you can then pass into filter-seqs without a --p-where quer…

And I tried to exclude the --p-where but then the same error appeared.

I didn't understand the solution reported in the post, for example how this clean-table.qza was generated and what it contains:

qiime feature-table filter-seqs
--i-data rep-seqs.qza
--i-table clean-table.qza
--o-filtered-data clean-rep-seqs.qza

How can I separate the bipolar for example to generate the ancombc graph with qiime composition da-barplot? Because I exported the ancombc and counted on the "p_val_slice.csv" that there are a lot of genus that passed the p-value < 0.05 for bipolar but when the graphic is generated it only seems to show the healthy.