Hi everybody,
I am using 2020.2 version and I am trying something new for me:
I grouped samples with a shared feature (in my case, seasons). I merged the dada2 table and it worked:
qiime feature-table group --i-table table-dada2.qza --p-axis sample --m-metadata-file metadata.tsv --m-metadata-column season --p-mode sum --o-grouped-table table-dada2-seasons2.qza
Now, i want to run beta and alpha diversity analyses:
qiime diversity core-metrics-phylogenetic \
--i-phylogeny rooted-tree.qza \
--i-table table-dada2-seasons2.qza \
--p-sampling-depth 100 \
--m-metadata-file metadata_merged.tsv \
--output-dir core-metrics-results
and I got this:
Plugin error from diversity:
None of the sample identifiers match between the metadata and the coordinates. Verify that you are using metadata and coordinates corresponding to the same dataset.
Debug info has been saved to /tmp/qiime2-q2cli-err-_kiexhsv.log
And the debug file:
/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/sklearn/metrics/pairwise.py:1735: DataConversionWarning: Data was converted to boolean for metric jaccard
warnings.warn(msg, DataConversionWarning)
Traceback (most recent call last):
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/q2cli/commands.py", line 328, in call
results = action(**arguments)
File "</home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/decorator.py:decorator-gen-386>", line 2, in core_metrics_phylogenetic
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 245, in bound_callable
output_types, provenance)
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 484, in callable_executor
outputs = self._callable(scope.ctx, **view_args)
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/q2_diversity/_core_metrics.py", line 53, in core_metrics_phylogenetic
metadata=metadata, n_jobs=n_jobs)
File "</home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/decorator.py:decorator-gen-483>", line 2, in core_metrics
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 245, in bound_callable
output_types, provenance)
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 484, in callable_executor
outputs = self._callable(scope.ctx, **view_args)
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/q2_diversity/_core_metrics.py", line 39, in core_metrics
results += emperor_plot(pcoa=pcoa, metadata=metadata)
File "</home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/decorator.py:decorator-gen-489>", line 2, in plot
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 245, in bound_callable
output_types, provenance)
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/qiime2/sdk/action.py", line 452, in callable_executor
ret_val = self._callable(output_dir=temp_dir, **view_args)
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/q2_emperor/_plot.py", line 65, in plot
custom_axes=custom_axes, plot_name='plot')
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/q2_emperor/_plot.py", line 41, in generic_plot
procrustes=procrustes, remote='.')
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/emperor/core.py", line 247, in init
ignore_missing_samples)
File "/home/qiime2/miniconda/envs/qiime2-2020.2/lib/python3.6/site-packages/emperor/core.py", line 325, in _validate_metadata
' to the same dataset.' % kind)
ValueError: None of the sample identifiers match between the metadata and the coordinates. Verify that you are using metadata and coordinates corresponding to the same dataset.
I also edited the metadata to fit to the new table but it doesn't work and I am not sure where I mistook in editing the metadata table. Is there a way to visualize dada2 qza so I can figure out how the metadata should look like.
Thank you very much!