Dada2 error -11 qiime2 2018.06

Hi there QIIME2 community,

I'm pretty new to QIIME 2 but ran through a couple of tutorials without any issues. Now that I am trying to run my own data I keep encountering one issue with dada2, and reading through other topics and trying those solutions has only changed the error code that dada2 has been returning. It seems for now I keep getting stuck on the following:

> qiime dada2 denoise-paired \
> --i-demultiplexed-seqs demux-paired-end.qza \
> --p-trim-left-f 20 \
> --p-trim-left-r 20 \
> --p-trunc-len-f 270 \
> --p-trunc-len-r 270 \
> --o-representative-sequences rep-seqs.qza \
> --o-table unfiltered-table.qza \
> --o-denoising-stats stats.qza

> Plugin error from dada2:                   
> 
>   An error was encountered while running DADA2 in R (return code -11), please inspect stdout and stderr to learn more.
> 
> Debug info has been saved to /tmp/qiime2-q2cli-err-41ramwjb.log

The following information is in the error log:

> 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/tmpa5etkafu/forward /tmp/tmpa5etkafu/reverse /tmp/tmpa5etkafu/output.tsv.biom /tmp/tmpa5etkafu/track.tsv /tmp/tmpa5etkafu/filt_f /tmp/tmpa5etkafu/filt_r 270 270 20 20 2.0 2 consensus 1.0 1 1000000
> 
> R version 3.4.1 (2017-06-30) 
> Loading required package: Rcpp
> DADA2 R package version: 1.6.0 
> 1) Filtering 
>  *** caught segfault ***
> address (nil), cause 'unknown'
> 
> Traceback:
>  1: .Call("_dada2_C_matchRef", PACKAGE = "dada2", seqs, ref, word_size,     non_overlapping)
>  2: C_matchRef(seqs, sq.phix, wordSize, nonOverlapping)
>  3: isPhiX(as(sread(fqR), "character"), ...)
>  4: (function (fn, fout, maxN = c(0, 0), truncQ = c(2, 2), truncLen = c(0,     0), maxLen = c(Inf, Inf), minLen = c(20, 20), trimLeft = c(0,     0), minQ = c(0, 0), maxEE = c(Inf, Inf), rm.phix = c(TRUE,     TRUE), matchIDs = FALSE, primer.fwd = NULL, id.sep = "\\s",     id.field = NULL, n = 1e+06, OMP = TRUE, compress = TRUE,     verbose = FALSE, ...) {    if (!OMP) {        ompthreads <- .Call(ShortRead:::.set_omp_threads, 1L)        on.exit(.Call(ShortRead:::.set_omp_threads, ompthreads))    }    if (!is.character(fn) || length(fn) != 2)         stop("Two paired input file names required.")    if (!is.character(fout) || length(fout) != 2)         stop("Two paired output file names required.")    if (any(duplicated(c(fn, fout)))) {        stop("The output and input file names must be different.")    }    for (var in c("maxN", "truncQ", "truncLen", "maxLen", "minLen",         "trimLeft", "minQ", "maxEE", "rm.phix")) {        if (length(get(var)) == 1) {            assign(var, c(get(var), get(var)))        }        if (length(get(var)) != 2) {            stop(paste("Input variable", var, "must be length 1 or 2 (Forward, Reverse)."))        }    }    startF <- max(1, trimLeft[[1]] + 1, na.rm = TRUE)    startR <- max(1, trimLeft[[2]] + 1, na.rm = TRUE)    endF <- truncLen[[1]]    if (endF < startF) {        endF = NA    }    endF <- endF - startF + 1    endR <- truncLen[[2]]    if (endR < startR) {        endR = NA    }    endR <- endR - startR + 1    fF <- FastqStreamer(fn[[1]], n = n)    on.exit(close(fF))    fR <- FastqStreamer(fn[[2]], n = n)    on.exit(close(fR), add = TRUE)    if (file.exists(fout[[1]])) {        if (file.remove(fout[[1]])) {            if (verbose)                 message("Overwriting file:", fout[[1]])        }        else {            stop("Failed to overwrite file:", fout[[1]])        }    }    if (file.exists(fout[[2]])) {        if (file.remove(fout[[2]])) {            if (verbose)                 message("Overwriting file:", fout[[2]])        }        else {            stop("Failed to overwrite file:", fout[[2]])        }    }    first = TRUE    remainderF <- ShortReadQ()    remainderR <- ShortReadQ()    casava <- "Undetermined"    inseqs = 0    outseqs = 0    while (TRUE) {        suppressWarnings(fqF <- yield(fF))        suppressWarnings(fqR <- yield(fR))        if (length(fqF) == 0 && length(fqR) == 0) {            break        }        inseqs <- inseqs + length(fqF)        if (matchIDs) {            if (first) {                if (is.null(id.field)) {                  id1 <- as.character(id(fqF)[[1]])                  id.fields <- strsplit(id1, id.sep)[[1]]                  ncolon <- sapply(gregexpr(":", id.fields),                     length)                  ncoltab <- table(ncolon)                  if (max(ncolon) == 6 && ncoltab["6"] == 1) {                    casava <- "Current"                    id.field <- which(ncolon == 6)                  }                  else if (max(ncolon) == 4 && ncoltab["4"] ==                     1) {                    casava <- "Old"                    id.field <- which(ncolon == 4)                  }                  else {                    stop("Couldn't automatically detect the sequence identifier field in the fastq id string.")                  }                }            }            else {                fqF <- append(remainderF, fqF)                fqR <- append(remainderR, fqR)            }        }        else {            if (length(fqF) != length(fqR))                 stop("Mismatched forward and reverse sequence files: ",                   length(fqF), ", ", length(fqR), ".")        }        if (matchIDs) {            idsF <- sapply(strsplit(as.character(id(fqF)), id.sep),                 `[`, id.field)            idsR <- sapply(strsplit(as.character(id(fqR)), id.sep),                 `[`, id.field)            if (casava == "Old") {                idsF <- sapply(strsplit(idsF, "#"), `[`, 1)            }            lastF <- max(c(0, which(idsF %in% idsR)))            lastR <- max(c(0, which(idsR %in% idsF)))            if (lastF < length(fqF)) {                remainderF <- fqF[(lastF + 1):length(fqF)]            }            else {                remainderF <- ShortReadQ()            }            if (lastR < length(fqR)) {                remainderR <- fqR[(lastR + 1):length(fqR)]            }            else {                remainderR <- ShortReadQ()            }            fqF <- fqF[idsF %in% idsR]            fqR <- fqR[idsR %in% idsF]        }        if (!is.null(primer.fwd)) {            barlen <- nchar(primer.fwd)            keepF <- narrow(sread(fqF), 1, barlen) == primer.fwd            keepR <- (narrow(sread(fqR), 1, barlen) == primer.fwd) &                 !keepF            fq <- ShortReadQ(sread = c(sread(fqF[keepF]), sread(fqR[keepR])),                 quality = c(quality(quality(fqF[keepF])), quality(quality(fqR[keepR]))),                 id = c(id(fqF[keepF]), id(fqR[keepR])))            fqR <- ShortReadQ(sread = c(sread(fqR[keepF]), sread(fqF[keepR])),                 quality = c(quality(quality(fqR[keepF])), quality(quality(fqF[keepR]))),                 id = c(id(fqR[keepF]), id(fqF[keepR])))            fqF <- fq            rm(fq)        }        if (is.finite(maxLen[[1]]) || is.finite(maxLen[[2]])) {            keep <- width(fqF) <= maxLen[[1]] & width(fqR) <=                 maxLen[[2]]            fqF <- fqF[keep]            fqR <- fqR[keep]        }        keep <- (width(fqF) >= startF & width(fqR) >= startR)        fqF <- fqF[keep]        fqF <- narrow(fqF, start = startF, end = NA)        fqR <- fqR[keep]        fqR <- narrow(fqR, start = startR, end = NA)        encF <- encoding(quality(fqF))        encR <- encoding(quality(fqR))        if (is.numeric(truncQ)) {            indF <- which(encF == truncQ[[1]])            indR <- which(encR == truncQ[[2]])            if (!(length(indF) == 1 && length(indR) == 1))                 stop("Encoding for this truncQ value not found.")            truncQ <- c(names(encF)[[indF]], names(encR)[[indR]])        }        if (length(fqF) > 0) {            rngF <- trimTails(fqF, 1, truncQ[[1]], ranges = TRUE)            fqF <- narrow(fqF, 1, end(rngF))        }        if (length(fqR) > 0) {            rngR <- trimTails(fqR, 1, truncQ[[2]], ranges = TRUE)            fqR <- narrow(fqR, 1, end(rngR))        }        truncQ <- c(encF[truncQ[1]], encR[truncQ[2]])        keep <- (width(fqF) > 0 & width(fqR) > 0)        fqF <- fqF[keep]        fqR <- fqR[keep]        keep <- rep(TRUE, length(fqF))        if (!is.na(endF)) {            keep <- keep & (width(fqF) >= endF)        }        if (!is.na(endR)) {            keep <- keep & (width(fqR) >= endR)        }        fqF <- fqF[keep]        fqR <- fqR[keep]        fqF <- narrow(fqF, start = 1, end = endF)        fqR <- narrow(fqR, start = 1, end = endR)        keep <- width(fqF) >= minLen[[1]] & width(fqR) >= minLen[[2]]        fqF <- fqF[keep]        fqR <- fqR[keep]        suppressWarnings(keep <- nFilter(maxN[[1]])(fqF) & nFilter(maxN[[2]])(fqR))        fqF <- fqF[keep]        fqR <- fqR[keep]        keep <- rep(TRUE, length(fqF))        qmat <- as(quality(fqF), "matrix")        if (minQ[[1]] > truncQ[[1]])             suppressWarnings(keep <- keep & (apply(qmat, 1, min) >                 minQ[[1]]))        if (maxEE[[1]] < Inf)             keep <- keep & C_matrixEE(qmat) <= maxEE[[1]]        qmat <- as(quality(fqR), "matrix")        if (minQ[[2]] > truncQ[[2]])             suppressWarnings(keep <- keep & (apply(qmat, 1, min) >                 minQ[[2]]))        if (maxEE[[2]] < Inf)             keep <- keep & C_matrixEE(qmat) <= maxEE[[2]]        fqF <- fqF[keep]        fqR <- fqR[keep]        rm(qmat)        if (length(fqF) != length(fqR))             stop("Filtering caused mismatch between forward and reverse sequence lists: ",                 length(fqF), ", ", length(fqR), ".")        if (rm.phix[[1]] && rm.phix[[2]]) {            is.phi <- isPhiX(as(sread(fqF), "character"), ...)            is.phi <- is.phi | isPhiX(as(sread(fqR), "character"),                 ...)        }        else if (rm.phix[[1]] && !rm.phix[[2]]) {            is.phi <- isPhiX(as(sread(fqF), "character"), ...)        }        else if (!rm.phix[[1]] && rm.phix[[2]]) {            is.phi <- isPhiX(as(sread(fqR), "character"), ...)        }        if (any(rm.phix)) {            fqF <- fqF[!is.phi]            fqR <- fqR[!is.phi]        }        outseqs <- outseqs + length(fqF)        if (first) {            writeFastq(fqF, fout[[1]], "w", compress = compress)            writeFastq(fqR, fout[[2]], "w", compress = compress)            first = FALSE        }        else {            writeFastq(fqF, fout[[1]], "a", compress = compress)            writeFastq(fqR, fout[[2]], "a", compress = compress)        }    }    if (outseqs == 0) {    }    if (verbose) {        outperc <- round(outseqs * 100/inseqs, 1)        outperc <- paste(" (", outperc, "%)", sep = "")        message("Read in ", inseqs, " paired-sequences, output ",             outseqs, outperc, " filtered paired-sequences.",             sep = "")    }    if (outseqs == 0) {        message(paste("The filter removed all reads:", fout[[1]],             "and", fout[[2]], "not written."))        file.remove(fout[[1]])        file.remove(fout[[2]])    }    return(invisible(c(reads.in = inseqs, reads.out = outseqs)))})(dots[[1L]][[1L]], dots[[2L]][[1L]], truncQ = 2L, truncLen = c(270L, 270L), trimLeft = c(20L, 20L), maxLen = Inf, minLen = 20, maxN = 0,     minQ = 0, maxEE = 2, rm.phix = TRUE, primer.fwd = NULL, matchIDs = FALSE,     id.sep = "\\s", id.field = NULL, n = 1e+05, OMP = TRUE, compress = TRUE,     verbose = FALSE)
>  5: .mapply(FUN, dots, MoreArgs)
>  6: FUN(X[[i]], ...)
>  7: lapply(X = X, FUN = FUN, ...)
>  8: mclapply(seq_len(n), do_one, mc.preschedule = mc.preschedule,     mc.set.seed = mc.set.seed, mc.silent = mc.silent, mc.cores = mc.cores,     mc.cleanup = mc.cleanup)
>  9: mcmapply(fastqPairedFilter, mapply(c, fwd, rev, SIMPLIFY = FALSE),     mapply(c, filt, filt.rev, SIMPLIFY = FALSE), MoreArgs = list(truncQ = truncQ,         truncLen = truncLen, trimLeft = trimLeft, maxLen = maxLen,         minLen = minLen, maxN = maxN, minQ = minQ, maxEE = maxEE,         rm.phix = rm.phix, primer.fwd = primer.fwd, matchIDs = matchIDs,         id.sep = id.sep, id.field = id.field, n = n, OMP = OMP,         compress = compress, verbose = verbose), mc.cores = ncores,     mc.silent = TRUE)
> 10: filterAndTrim(unfiltsF, filtsF, unfiltsR, filtsR, truncLen = c(truncLenF,     truncLenR), trimLeft = c(trimLeftF, trimLeftR), maxEE = maxEE,     truncQ = truncQ, rm.phix = TRUE, multithread = multithread)
> 11: withCallingHandlers(expr, warning = function(w) invokeRestart("muffleWarning"))
> 12: suppressWarnings(filterAndTrim(unfiltsF, filtsF, unfiltsR, filtsR,     truncLen = c(truncLenF, truncLenR), trimLeft = c(trimLeftF,         trimLeftR), maxEE = maxEE, truncQ = truncQ, rm.phix = TRUE,     multithread = multithread))
> An irrecoverable exception occurred. R is aborting now ...
> Traceback (most recent call last):
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2_dada2/_denoise.py", line 229, in denoise_paired
>     run_commands([cmd])
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2_dada2/_denoise.py", line 36, in run_commands
>     subprocess.run(cmd, check=True)
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/subprocess.py", line 398, in run
>     output=stdout, stderr=stderr)
> subprocess.CalledProcessError: Command '['run_dada_paired.R', '/tmp/tmpa5etkafu/forward', '/tmp/tmpa5etkafu/reverse', '/tmp/tmpa5etkafu/output.tsv.biom', '/tmp/tmpa5etkafu/track.tsv', '/tmp/tmpa5etkafu/filt_f', '/tmp/tmpa5etkafu/filt_r', '270', '270', '20', '20', '2.0', '2', 'consensus', '1.0', '1', '1000000']' returned non-zero exit status -11
> 
> During handling of the above exception, another exception occurred:
> 
> Traceback (most recent call last):
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2cli/commands.py", line 274, in __call__
>     results = action(**arguments)
>   File "<decorator-gen-380>", line 2, in denoise_paired
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/qiime2/sdk/action.py", line 232, in bound_callable
>     output_types, provenance)
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/qiime2/sdk/action.py", line 367, in _callable_executor_
>     output_views = self._callable(**view_args)
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2_dada2/_denoise.py", line 244, in denoise_paired
>     " and stderr to learn more." % e.returncode)
> Exception: An error was encountered while running DADA2 in R (return code -11), please inspect stdout and stderr to learn more.

The data I am trying to analyse is comprised of many paired fastq files, which I have imported using:

> qiime tools import --type 'SampleData[PairedEndSequencesWithQuality]' --input-path raw/ --source-format CasavaOneEightSingleLanePerSampleDirFmt --output-path demux-paired-end.qza

Is there anybody that can help me out here? I have tried the following solutions from other topics:

The last command couldn't run all the way till the end, as a lot of the URLs returned "404 not found". The command is for an older version of QIIME 2, so I thought maybe that's why? Anyway, since it did overwrite a bunch of stuff, I tried my command again and I got a little bit further, and my computer ran for 2 days straight until I came home to the bright red error message once again (grr!). Here is the latest error log file for this:

> 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/tmpyy5l777i/forward /tmp/tmpyy5l777i/reverse /tmp/tmpyy5l777i/output.tsv.biom /tmp/tmpyy5l777i/track.tsv /tmp/tmpyy5l777i/filt_f /tmp/tmpyy5l777i/filt_r 270 270 20 20 2.0 2 consensus 1.0 1 1000000
> 
> R version 3.4.1 (2017-06-30) 
> Loading required package: Rcpp
> DADA2 R package version: 1.6.0 
> 1) Filtering ..................................................
> 2) Learning Error Rates
> 2a) Forward Reads
> Initializing error rates to maximum possible estimate.
> Sample 1 - 7601 reads in 5793 unique sequences.
> Sample 2 - 4809 reads in 3892 unique sequences.
> Sample 3 - 7806 reads in 5801 unique sequences.
> Sample 4 - 6017 reads in 4632 unique sequences.
> Sample 5 - 3728 reads in 3191 unique sequences.
> Sample 6 - 4592 reads in 3711 unique sequences.
> Sample 7 - 4100 reads in 3613 unique sequences.
> Sample 8 - 4574 reads in 3527 unique sequences.
> Sample 9 - 6076 reads in 3304 unique sequences.
> Sample 10 - 4625 reads in 3655 unique sequences.
> Sample 11 - 4649 reads in 3541 unique sequences.
> Sample 12 - 9846 reads in 7379 unique sequences.
> Sample 13 - 10766 reads in 8500 unique sequences.
> Sample 14 - 5510 reads in 4475 unique sequences.
> Sample 15 - 8833 reads in 6268 unique sequences.
> Sample 16 - 7700 reads in 5483 unique sequences.
> Sample 17 - 4720 reads in 3405 unique sequences.
> Sample 18 - 48073 reads in 23165 unique sequences.
> Sample 19 - 69307 reads in 34940 unique sequences.
> Sample 20 - 35694 reads in 21669 unique sequences.
> Sample 21 - 57885 reads in 25015 unique sequences.
> Sample 22 - 63690 reads in 26008 unique sequences.
> Sample 23 - 70913 reads in 32543 unique sequences.
> Sample 24 - 71703 reads in 32864 unique sequences.
> Sample 25 - 41274 reads in 18804 unique sequences.
> Sample 26 - 81075 reads in 35381 unique sequences.
> Sample 27 - 59062 reads in 28023 unique sequences.
> Sample 28 - 69213 reads in 28648 unique sequences.
> Sample 29 - 65479 reads in 29352 unique sequences.
> Sample 30 - 1639 reads in 1487 unique sequences.
> Sample 31 - 1446 reads in 1290 unique sequences.
> Sample 32 - 1487 reads in 1405 unique sequences.
> Sample 33 - 1122 reads in 1070 unique sequences.
> Sample 34 - 1508 reads in 1340 unique sequences.
> Sample 35 - 1037 reads in 889 unique sequences.
> Sample 36 - 1233 reads in 1179 unique sequences.
> Sample 37 - 646 reads in 606 unique sequences.
> Sample 38 - 834 reads in 795 unique sequences.
> Sample 39 - 1506 reads in 1379 unique sequences.
> Sample 40 - 2446 reads in 2169 unique sequences.
> Sample 41 - 4450 reads in 3768 unique sequences.
> Sample 42 - 3324 reads in 3005 unique sequences.
> Sample 43 - 5128 reads in 4339 unique sequences.
> Sample 44 - 4228 reads in 3685 unique sequences.
> Sample 45 - 3426 reads in 2935 unique sequences.
> Sample 46 - 4717 reads in 3891 unique sequences.
> Sample 47 - 21089 reads in 14368 unique sequences.
> Sample 48 - 11007 reads in 9181 unique sequences.
> Sample 49 - 3811 reads in 3384 unique sequences.
> Sample 50 - 5319 reads in 4818 unique sequences.
>    selfConsist step 2 
>    selfConsist step 3 
>    selfConsist step 4 
>    selfConsist step 5 
>    selfConsist step 6 
>    selfConsist step 7 
>    selfConsist step 8 
> 
>  *** caught segfault ***
> address (nil), cause 'unknown'
> 
> Traceback:
>  1: .Call("_dada2_dada_uniques", PACKAGE = "dada2", seqs, abundances,     err, quals, score, gap, use_kmers, kdist_cutoff, band_size,     omegaA, max_clust, min_fold, min_hamming, min_abund, use_quals,     final_consensus, vectorized_alignment, homo_gap, multithread,     verbose, SSE)
>  2: dada_uniques(names(derep[[i]]$uniques), unname(derep[[i]]$uniques),     err, qi, opts[["SCORE_MATRIX"]], opts[["GAP_PENALTY"]], opts[["USE_KMERS"]],     opts[["KDIST_CUTOFF"]], opts[["BAND_SIZE"]], opts[["OMEGA_A"]],     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"]])
>  3: dada(drpsF, err = NULL, selfConsist = TRUE, multithread = multithread,     VECTORIZED_ALIGNMENT = FALSE, SSE = 1)
> An irrecoverable exception occurred. R is aborting now ...
> Traceback (most recent call last):
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2_dada2/_denoise.py", line 229, in denoise_paired
>     run_commands([cmd])
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2_dada2/_denoise.py", line 36, in run_commands
>     subprocess.run(cmd, check=True)
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/subprocess.py", line 398, in run
>     output=stdout, stderr=stderr)
> subprocess.CalledProcessError: Command '['run_dada_paired.R', '/tmp/tmpyy5l777i/forward', '/tmp/tmpyy5l777i/reverse', '/tmp/tmpyy5l777i/output.tsv.biom', '/tmp/tmpyy5l777i/track.tsv', '/tmp/tmpyy5l777i/filt_f', '/tmp/tmpyy5l777i/filt_r', '270', '270', '20', '20', '2.0', '2', 'consensus', '1.0', '1', '1000000']' returned non-zero exit status -11
> 
> During handling of the above exception, another exception occurred:
> 
> Traceback (most recent call last):
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2cli/commands.py", line 274, in __call__
>     results = action(**arguments)
>   File "<decorator-gen-380>", line 2, in denoise_paired
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/qiime2/sdk/action.py", line 232, in bound_callable
>     output_types, provenance)
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/qiime2/sdk/action.py", line 367, in _callable_executor_
>     output_views = self._callable(**view_args)
>   File "/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2_dada2/_denoise.py", line 244, in denoise_paired
>     " and stderr to learn more." % e.returncode)
> Exception: An error was encountered while running DADA2 in R (return code -11), please inspect stdout and stderr to learn more.

Sorry, that's a lot of error log files all at once, but I'm hoping someone can make some sense out of it.

I'd appreciate any help!

Cheers,
Bobby

Welcome! :houses:

I don't think we have seen this error yet, would you be able to share a link to demux-paired-end.qza so that we can recreate the error? Feel free to send to me in a DM if you don't want to share publicly.

Can you tell us a bit more about your computation environment? Linux? Mac? Cluster? How much RAM? Etc.

:qiime2: :exclamation:

Thanks so much for trying to resolve on your own before posting this question!

That would be my guess, too.

Ah bummer! So one potential option for speeding up runtime is to use the --p-n-threads option (this value will depend on your computation environment, see my questions above).

Better to be thorough, I always say! Thanks! Unfortunately there isn't much we can do without getting our hands on data, since this is a new one for us. Thanks! :t_rex:

1 Like

Thank you!

Here is a link to my demux-paired-end.qza:
https://drive.google.com/open?id=1hN5h2GNt8mHbVuNyqHoj32Su9JpiDOWc

I’ve got a Windows 10 PC so I’m running QIIME 2 in a Linux Ubuntu (64-bit) virtual machine, which I have appointed 8.5GB of RAM (my PC has got 16 GB of RAM so I could even give it a bit more). I’m using Oracle Virtualbox for this.

I’m curious to hear how you get on with the file!If it would be easier, I could make a different dataset with only a few samples to do tests with. I thought about doing this myself but then went “ah, if it works right away it would be great that I’ve done the whole dataset!” But I guess it never works that way, does it!

Hey there @bobby!

Thanks for the files, and the details about your computational environment. I am not sure what is wrong, but it is almost certainly related to the environment. Perhaps it would make sense to start from a fresh VM? Maybe some setting or config was messed up somehow. Another option is that 8.5 GB isn't enough.
FWIW, I was able to successfully denoise your samples while attempting to debug the issue, which I think rules out a problem with the data (which was my original suspicion).

denoising_stats.qza (10.8 KB)
table.qza (166.6 KB)
representative_sequences.qza (482.7 KB)

I haven't looked at these at all, but figured I would share with you.

Hi @thermokarst!

Thank you for your help, and thanks so much for sharing the output files with me! I’ll have a look at them, curious to see what it looks like!

I will try and start with a fresh VM before I try again, and give it some more RAM too. But it’s nice to know it’s not the data!

Thanks again!

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