Hi,
I know that there are pre - trained classifiers for SILVA but I was attempting to run a 16S vs 18S only comparison. I downloaded the package from SILVA's website and began training the classifier. They provided me rep - set FASTA files for 16S and 18S only along with taxonomy (consensus, majority and all taxonomy) files for 16S and 18S only. Once I assembled one, I attempted to apply it to my rep-seqs.qza but obtain this error:
this classifier does not support confidence values.
Log:
Traceback (most recent call last):
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/q2cli/commands.py", line 328, in call
results = action(**arguments)
File "</home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/decorator.py:decorator-gen-347>", line 2, in classify_sklearn
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/qiime2/sdk/action.py", line 240, in bound_callable
output_types, provenance)
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/qiime2/sdk/action.py", line 383, in callable_executor
output_views = self._callable(**view_args)
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/q2_feature_classifier/classifier.py", line 215, in classify_sklearn
reads, classifier, read_orientation=read_orientation)
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/q2_feature_classifier/classifier.py", line 170, in _autodetect_orientation
result = list(zip(*predict(first_n_reads, classifier, confidence=0.)))
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/q2_feature_classifier/_skl.py", line 45, in predict
for chunk in _chunks(reads, chunk_size)) for m in c)
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/joblib/parallel.py", line 1003, in call
if self.dispatch_one_batch(iterator):
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/joblib/parallel.py", line 834, in dispatch_one_batch
self._dispatch(tasks)
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/joblib/parallel.py", line 753, in _dispatch
job = self._backend.apply_async(batch, callback=cb)
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 201, in apply_async
result = ImmediateResult(func)
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/joblib/_parallel_backends.py", line 582, in init
self.results = batch()
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/joblib/parallel.py", line 256, in call
for func, args, kwargs in self.items]
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/joblib/parallel.py", line 256, in
for func, args, kwargs in self.items]
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/q2_feature_classifier/_skl.py", line 52, in _predict_chunk
return _predict_chunk_with_conf(pipeline, separator, confidence, chunk)
File "/home/sabasu/miniconda2/envs/qiime2-2019.10/lib/python3.6/site-packages/q2_feature_classifier/_skl.py", line 68, in _predict_chunk_with_conf
raise ValueError('this classifier does not support confidence values')
ValueError: this classifier does not support confidence values
My commands:
qiime tools import
--type 'FeatureData[Sequence]'
--input-path silva_132_99_16S.fna
--output-path silva-16s.qza
qiime tools import
--type 'FeatureData[Taxonomy]'
--input-format HeaderlessTSVTaxonomyFormat
--input-path 16S_consensus_taxonomy_7_levels.txt
--output-path silva-16s-txt-taxonomy.qza
qiime feature-classifier extract-reads
--i-sequences silva-16s.qza
--p-f-primer CGAGAAGACCCTATGGAGCTT
--p-r-primer AATCGTTGAACAAACGAACC
--o-reads silva-16s-ref-seqs.qza
qiime feature-classifier classify-sklearn
--i-classifier silva-16s-classifier.qza
--i-reads rep-seqs-dada2.qza
--o-classification 16s-taxonomy.qza
The last command ends in an error. Any help would be much appreciated.