Regarding errors with denoise in MiSeq runs

[Pnmrc (Pamela M)]

Hi all,
I am trying to get past through the denoise part. I have a MiSeq V4 sequencing done and I am decided arbitarily (more from FASTQC) to use 130 as my truncating length. I have also tried with 150. This is my command:

qiime dada2 denoise-paired --i-demultiplexed-seqs demux-paired-end2.qza --p-trim-left-r 0 --p-trim-left-f 0 --p-trunc-len-f 130 --p-trunc-len-r 130 --o-representative-sequences req-seqs.qza --o-table table2.qza --p-n-threads 20 --o-denoising-stats
STATS_FILE2.qza

And the error I run into:
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.

Command: run_dada_paired.R /tmp/tmp1hg9eoac/forward /tmp/tmp1hg9eoac/reverse /tmp/tmp1hg9eoac/output.tsv.biom /tmp/tmp1hg9eoac/track.tsv /tmp/tmp1hg9eoac/filt_f /tmp/tmp1hg9eoac/filt_r 150 150 0 0 2.0 2.0 2 consensus 1.0 20 1000000

R version 3.5.1 (2018-07-02)
Loading required package: Rcpp
DADA2: 1.10.0 / Rcpp: 1.0.2 / RcppParallel: 4.4.4

1. Filtering Error in names(answer) <- names1 :
   ‘names’ attribute [4] must be the same length as the vector [3]
   Execution halted
   Traceback (most recent call last):
   File “anaconda3/envs/qiime2-2019.10/lib/python3.6/site-packages/q2_dada2/_denoise.py”, line 257, in denoise_paired
   run_commands([cmd])
   File “anaconda3/envs/qiime2-2019.10/lib/python3.6/site-packages/q2_dada2/_denoise.py”, line 36, in run_commands
   subprocess.run(cmd, check=True)
   File “anaconda3/envs/qiime2-2019.10/lib/python3.6/subprocess.py”, line 418, in run
   output=stdout, stderr=stderr)
   subprocess.CalledProcessError: Command ‘[‘run_dada_paired.R’, ‘/tmp/tmp1hg9eoac/forward’, ‘/tmp/tmp1hg9eoac/reverse’, ‘/tmp/tmp1hg9eoac/output.tsv.biom’, ‘/tmp/tmp1hg9eoac/track.tsv’, ‘/tmp/tmp1hg9eoac/filt_f’, ‘/tmp/tmp1hg9eoac/filt_r’, ‘150’, ‘150’, ‘0’, ‘0’, ‘2.0’, ‘2.0’, ‘2’, ‘consensus’, ‘1.0’, ‘20’, ‘1000000’]’ returned non-zero exit status 1.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File “/anaconda3/envs/qiime2-2019.10/lib/python3.6/site-packages/q2cli/commands.py”, line 328, in call
results = action(**arguments)
File “</anaconda3/envs/qiime2-2019.10/lib/python3.6/site-packages/decorator.py:decorator-gen-459>”, line 2, in denoise_paired
File “/anaconda3/envs/qiime2-2019.10/lib/python3.6/site-packages/qiime2/sdk/action.py”, line 240, in bound_callable
output_types, provenance)
File “/anaconda3/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 “anaconda3/envs/qiime2-2019.10/lib/python3.6/site-packages/q2_dada2/_denoise.py”, line 272, in denoise_paired
" and stderr to learn more." % e.returncode)
Exception: An error was encountered while running DADA2 in R (return code 1), please inspect stdout and stderr to learn more.

Can you please help me with this? Looks like denoising is the common step for error.

Thanks,
Pamela

[ChrisKeefe]

Welcome to the forum, @Pnmrc!

I did a quick search on this forum for your error:

@Pnmrc

Filtering Error in names(answer) <- names1 :
‘names’ attribute [4] must be the same length as the vector [3]

I suspect it's a cryptic out-of-memory error, caused by running this command with many cores.

Denoising error, names attribute must be the same length as vector

Hi @Roger_Huerlimann, Congratulations for running into one of the more cryptic error messages that dada2 can throw at you. This is effectively a memory error even though it does not look like one — or more specifically a multithreading issue that can be fixed by reducing the number of threads used. See here for some discussion: I think the dada2 version was upgraded somewhere in there, so it could be a version issue, but it could also be coincidence. Reduce the number of threads you are …

Try re-running with fewer cores, and let us know how it goes!

Best,
Chris