Dada remove sequencing error -> Fatal error: Exit code 139 ()

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I’ve used the dada2 workflow to analyse 16S rRNA sequences and at the step ‘dada Remove sequencing errors’ (Galaxy Version 1.34.0+galaxy0), I get the following error message for my reverse reads only:

 *** caught segfault ***
address 0x14b058ea9000, cause 'memory not mapped'

Traceback:
 1: dada_uniques(names(drpi$uniques), unname(drpi$uniques), names(drpi$uniques) %in%     c(priors, pseudo_priors), erri, unname(t(drpi$quals)), opts[["MATCH"]],     opts[["MISMATCH"]], opts[["GAP_PENALTY"]], opts[["USE_KMERS"]],     opts[["KDIST_CUTOFF"]], opts[["BAND_SIZE"]], opts[["OMEGA_A"]],     opts[["OMEGA_P"]], opts[["OMEGA_C"]], opts[["DETECT_SINGLETONS"]],     if (initializeErr) {        1    } else {        opts[["MAX_CLUST"]]    }, opts[["MIN_FOLD"]], opts[["MIN_HAMMING"]], opts[["MIN_ABUNDANCE"]],     TRUE, FALSE, opts[["VECTORIZED_ALIGNMENT"]], opts[["HOMOPOLYMER_GAP_PENALTY"]],     multithread, (verbose >= 2), opts[["SSE"]], opts[["GAPLESS"]],     opts[["GREEDY"]])
 2: dada(derep, err, pool = pool, multithread = nthreads)
An irrecoverable exception occurred. R is aborting now ...
/data/jwd07/main/090/412/90412093/tool_script.sh: line 28: 1484767 Segmentation fault      (core dumped) Rscript '/data/jwd07/main/090/412/90412093/configs/tmph1bqqk66' ${GALAXY_SLOTS:-1}
Job Message:

  • desc: Fatal error: Exit code 139 ()

  • error_level: 3

  • type: exit_code

  • exit_code: 139

What could be the source of this error?

Thanks!

2

Welcome @Cecile_M

This error either indicates 1) some format problem with the fastq reads or 2) an unusually large job process that terminated the tool. The first is much more common but the second would be possible with this specific tool when running in “pooled” mode.

So, first, try a rerun. A few jobs will fail by chance!

If that still fails, you can try running each sample individually (instead of pooled) to see what happens. This will involve still submitting the collection, but using the toggle on top of the form to run in the other mode. If this runs successfully, it would be a good test: is there some problem in the data format to correct (for one or more samples) versus an issue with the pooled content job growing unusually large. You may be able to notice why pooled would be computationally challenging in the output reports.

Let us know what happens! You can welcome to share back the job for review, too! :slight_smile: