I get this error from Qiime2 after the dada2 denoise ran for 2 weeks. Could you please let me know how to resolve this issue? I would really appreciate.
Remove chimeras (method = consensus)
Traceback (most recent call last):
File “/root/miniconda2/envs/qiime2-2019.1/lib/python3.6/site-packages/q2cli/commands.py”, line 274, in call
results = action(**arguments)
File “</root/miniconda2/envs/qiime2-2019.1/lib/python3.6/site-packages/decorator.py:decorator-gen-442>”, line 2, in denoise_paired
File “/root/miniconda2/envs/qiime2-2019.1/lib/python3.6/site-packages/qiime2/sdk/action.py”, line 231, in bound_callable
File “/root/miniconda2/envs/qiime2-2019.1/lib/python3.6/site-packages/qiime2/sdk/action.py”, line 389, in callable_executor
prov = provenance.fork(name)
File “/root/miniconda2/envs/qiime2-2019.1/lib/python3.6/site-packages/qiime2/core/archive/provenance.py”, line 423, in fork
forked = super().fork()
File “/root/miniconda2/envs/qiime2-2019.1/lib/python3.6/site-packages/qiime2/core/archive/provenance.py”, line 326, in fork
File “/root/miniconda2/envs/qiime2-2019.1/lib/python3.6/distutils/dir_util.py”, line 124, in copy_tree
“cannot copy tree ‘%s’: not a directory” % src)
distutils.errors.DistutilsFileError: cannot copy tree ‘/tmp/qiime2-provenance-03mgxmp4’: not a directory
Plugin error from dada2:
cannot copy tree ‘/tmp/qiime2-provenance-03mgxmp4’: not a directory
See above for debug info.
Running external command line application(s). This may print messages to stdout and/or stderr.
The command(s) being run are below. These commands cannot be manually re-run as they will depend on temporary files that no longer exist.
Sounds like QIIME 2 couldn't find the temporary files from this command (read on)...
That is probably the answer why! I suspect your host OS "cleaned up" some of the temporary files too soon. We don't see that often, but it does come up every now and then (macOS is usually the culprit, though).
What was the command you ran? Copy and paste please. One workaround is to re-run, but after setting the $TMPDIR env var to another (non-os owned) location. As well, I wonder if we can speed the command up by setting some --p-n-threads...
The difference in the dataset is that the cDNA paired end illumina sequenced data belonging to bacteria in water sample was sequenced only for V4 region of the bacteria; whereas, the DNA data was sequenced for all variable regions of the bacteria, hence in my understanding the cDNA went fast and DNA takes time. Do you agree?
By changing the tmp dir do you mean:
in the current terminal, if I want to make it last long, I can put it in the .bashrc file? Just in case, the terminal gets closed accidentally.
Seems pretty reasonable, although your quality profiles looks pretty strange — the lack of any real distribution of quality scores leads me to believe that these sequences have had some kind of quality-control step applied to them already. DADA2 is designed to work with the original noisy reads — that is how it builds the error profile. If my hunch is right and these reads have been altered, I would suggest you get your hands on the source data (pre-qa/qc), and try from there.
(Matthew Ryan Dillon)
I strongly encourage you to reach out to your sequencing center — those error profiles look like the product of some cleanup effort. Not that that is necessarily a problem, but, if it were me, I would want to know!
All non-biological sequences need to be removed from reads prior to using DADA2 (this includes primers).
Thanks, I will consult with the data provider but, can you please be more specific on why you think the data has been through quality control. Your explanation will help me to understand the intricacies of the analysis. Thanks!
Yep, of course, I actually provided that information above:
So, the concern here is that pretty much all positions in your reads are showing similar, very narrow, ranges in quality scores. This is not what we usually see in the wild, particularly with Illumina data (can you clarify your sequencing platform, by the way?) Normally we see a much more "natural" spread of quality scores. A good example of this spread can be seen here. Hope that helps!