Hi EAGER team, I wanted to bring to your attention an error that recently occurred with CircularMapper (CM) in EAGER

v2.5.3

. I know y'all are super busy with

v3

development, so I don't expect anyone to necessarily troubleshoot this with me, but I thought to bring it up so it can be checked/tested in

v3

before release (in fact, I would be happy to test if possible). v3 development is also the reason I didn't post this as an issue on GitHub, but I'd be happy to do that if preferred. The main error is this at the circularmapper step:

Exception in thread "main" java.lang.IllegalArgumentException: Reference index for 'SJYQ01000001.1' not found in sequence dictionary.

, even though it is present in the

*.dict

file and the

*.dict

file is of course present and named correctly. I've attached an example

stdout

file with this message and associated

log

file. This happened with different reference genomes, so not just this one. I couldn't find this error reported before in the EAGER or CM GitHub issues, or via google search, so I thought I'd bring it up here. I was also able to replicate the error when using the standalone version of CM

v1.93.5

. The specific flag that causes it is setting

--filterNonCircularSequences true

with

realign-1.93.5.jar

. This is also the setting that caused the error in EAGER (

circularfilter = true

). When

false

both standalone CM and EAGER run without error. The weird thing is though, that I used the exact same environment setup last year with this option set to

true

and it worked as expected, though with different samples and reference genomes.

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https://github.com/nf-core/eager/blob/dev/nf-test.config#L11-L12 @Thiseas C. Lamnidis

Hi all, I’m currently setting up nf-core/eager on our HPC cluster (Apollo at CBiB, Bordeaux, France) and had a question regarding disk usage. We are working on ancient DNA data, mainly human (but also including some animal, plant, and pathogen samples). Our sequencing batches can include a mix of capture data and low-coverage genomes processed together on the same run. Each batch typically corresponds to ~100–150 GB of raw FASTQ data. While testing eager, we noticed that the

work/

directory becomes very large during execution (several hundreds of GB to Tb). I understand this is due to intermediate BAM files and Nextflow caching, but I wanted to check: • Is this scale of disk usage (e.g. 1 TB for ~150 GB input) expected? • Do you have a rough estimate or rule of thumb for the size of the work directory depending on input data and typical parameters? We’re currently discussing storage solutions with our HPC admins, so any guidance would be very helpful. Thanks a lot for your help and for the pipeline! Best,

Hi everyone, I’m currently testing

nf-core/eager

on our HPC cluster (IBEX) using Singularity and Slurm, and the pipeline stops at the MALT metagenomics profiling step:

NFCORE_EAGER:EAGER:METAGENOMICS:METAGENOMICS_PROFILING:MALT_RUN (doublestranded_0)

The error seems to be related to Java memory:

java.lang.OutOfMemoryError: Java heap space

From the Slurm report, the job used around ~273 GB of memory, but it looks like MALT may not be receiving enough Java heap memory inside the container. I was wondering where would be the best place to add extra Java memory options for this process in

nf-core/eager

? For example, should I set something like:

JAVA_TOOL_OPTIONS="-Xmx700G"
_JAVA_OPTIONS="-Xmx700G"
INSTALL4J_ADD_VM_PARAMS="-Xmx700G"

inside my Slurm submission script, in a custom Nextflow config using

withName: '.*MALT_RUN.*'

, or somewhere else? For context, I’m running the dev version/revision:

nf-core/eager 3.0.0dev
revision: f77d2464a7c6fe06b67ce1832f2fe72ba21c8fde

and the metagenomics settings include:

--run_metagenomics
--metagenomics_profiling_tool malt
--metagenomics_profiling_database /path/to/MALT_index
--metagenomics_malt_memorymode map

Any advice on the recommended way to increase Java heap memory specifically for MALT would be greatly appreciated. Thank you!

Hi all! I looked back through the messages but can't seem to see the exact solution to my problem:

Error executing process > 'multiqc (1)'

Caused by:
  Process `multiqc` input file name collision -- There are multiple input files for each of the following file names: [long list of files here]

I have some quite large raw files, so I ended up splitting them into parts (with seqkit). So in my .input.tsv I have, say:

Sample_Name	Library_ID
NS0118	NS0118_part1
NS0118	NS0118_part2
NS0061_2025	NS0061_2025_part1
NS0061_2025	NS0061_2025_part2
NS0061_2023	NS0061_2023_part1
NS0061_2023	NS0061_2023_part2

Q1: Perhaps the duplicated sample IDs are causing problems for multiqc...? Also, in this case I have many sequencing runs of the same individual. Q2: what's the best way to merge the all data into one final genome?

Hi, everybody! Has anyone encountered any kind of problem with inconsistent steps in a pipeline succeeding and failing with no apparent pattern? I am having problems with

damageprofiler.

I'm running nf-core/eager, v2.5.1 using Nextflow v22.10.6 with DSL1. I have three samples from the same sequencing run that are pretty similar to each other in terms of size (after clipping they each have from 145 to 175million reads), quality and reads average length. I ran nf-core/eager separately for each of them. Sample 1 worked on first try in 15 minutes; Sample 2 first failed 3 times (submitted damage profiler 4 times, canceling it after 1.5 hours). I got impatient, canceled the run and re-sent it and then it succeeded after two tries (failed one was 1 hour long, the second, successful one, lasted 25 minutes). Sample 3 is still running but has failed already 3 times with a similar pattern as sample 2. All failed runs display the same error message (memory problems):

Exception in thread "main" java.lang.OutOfMemoryError: GC overhead limit exceeded
	at htsjdk.samtools.util.StringUtil.bytesToString(StringUtil.java:301)
	at htsjdk.samtools.BAMRecord.decodeReadName(BAMRecord.java:440)
	at htsjdk.samtools.BAMRecord.getReadName(BAMRecord.java:252)
	at htsjdk.samtools.SAMUtils.validateCigar(SAMUtils.java:937)
	at htsjdk.samtools.SAMRecord.validateCigar(SAMRecord.java:1807)
	at htsjdk.samtools.BAMRecord.getCigar(BAMRecord.java:284)
	at htsjdk.samtools.SAMRecord.isValid(SAMRecord.java:2103)
	at htsjdk.samtools.BAMFileReader$BAMFileIterator.advance(BAMFileReader.java:848)
	at htsjdk.samtools.BAMFileReader$BAMFileIterator.next(BAMFileReader.java:834)
	at htsjdk.samtools.BAMFileReader$BAMFileIterator.next(BAMFileReader.java:802)
	at htsjdk.samtools.SamReader$AssertingIterator.next(SamReader.java:574)
	at htsjdk.samtools.SamReader$AssertingIterator.next(SamReader.java:553)
	at calculations.DamageProfiler.extractSAMRecords(DamageProfiler.java:107)
	at calculations.StartCalculations.start(StartCalculations.java:298)
	at RunDamageProfiler.main(RunDamageProfiler.java:37)

I'm confused because all samples and all tries have had the same resources (16 CPUs and 20GB of memory) and sent the same command (I checked in the work/ directories in the .sh file), and they fail randomly. The only certain thing is that if damageprofiler takes more than 30 minutes it will fail, but I'd like to avoid having runs stuck on a step over and over if I can help it. One thing that I've noticed, though, is that sample 2 and 3 both got scheduled on the same HPC node (not at the same time): could that be the problem? Thank you for anybody that has an idea!

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Hi there! I'm trying to run eager to remove host contaminants, and I'm not sure if the program ran to completion or not? Here is my command:

nextflow run nf-core/eager \
-profile fsu_draco \
--input '00_raw/*_{1,2}.fastq' \
--fasta '/home/user/fastq/references/GRCh38.14/GCF_000001405.40_GRCh38.p14_genomic.fna' \
--hostremoval_input_fastq

And here is the error output I got:

ERROR: Failed to open file: ../data/subsampled/ERR5766177_PE.mapped.hostremoved.fwd.fq_subsample_1000000.fastq.gz

But in the output, it says the pipeline ran to completion:

-[nf-core/eager] Pipeline completed successfully-
-[nf-core/eager] MultiQC run report can be found in ./results/multiqc -
-[nf-core/eager] Further output documentation can be seen at <https://nf-core/eager/output> -
WARN: Graphviz is required to render the execution DAG in the given format -- See <http://www.graphviz.org> for more info.
Completed at: 05-Jul-2026 06:18:10
Duration    : 14h 8m 30s
CPU hours   : 73.1 (21.9% failed)
Succeeded   : 18
Failed      : 1

From the tutorial I'm following (spaam-community.org/intro-to-ancient-metagenomics-book/taxonomic-profiling.html), there should be a "data" folder in the output, but I don't have one. Can I trust the fastq files in

results/hostremoved_fastq/

to be what I need?

Oh dear... It wasn't an error from the pipeline, I just copy pasted the next line from the tutorial and forgot to comment it before running my script. 🤦 All my apologies. Problem solved, great start of the week! 😂

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I need to prepare (PE) sequencing data for an ENA upload, and since they request data to be adapter-clipped (but not processed in any other way), I was wondering if I can just run eager with the following flags:

--clip_min_read_quality 0 \
--skip_collapse \
--preserve5p \

or would you simply run adapterremoval outside of the pipeline?

Hi Marcel! Yes, you can run eager for ena prep. You can see my suggested settings here: https://github.com/nf-core/configs/blob/master/conf%2Fpipeline%2Feager%2Feva.config#L604-L623 This will also map your non-filtered data, as there is no way to turn mapping off. To avoid that, your only option is to run AR standalone.

should also mention that @Maxime Borry had created a dedicated enaprep Nextflow pipeline, which you can find on his github. that would be another option to avoid mapping

excellent, thank you!

Hello everyone, my name is Mert. I am trying to reproduce the results of papers that use the EAGER pipeline. However, I haven't been able to find any papers on Google Scholar that clearly show their intermediate results. If you know of any such papers, could you please help me out? I would ideally need a paper that shares a complete MultiQC report (perhaps in the supplementary data), or at least includes specific module outputs as figures, such as a mapDamage plot. Thanks!

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Hi Everyone, I have run early eager for small dataset (in coverage and sample), but now i am analysing whole genome with pretty good coverage, so problem is like at 4 hrs interval everything get failed, start running again. As i have read documents, its like its running intially with some default resource, if it does not get succeed, it will increase the resource and run. here with each time, it will make new file as i have seen directly and taking extra space, also i am loosing time, as i know i have dense data with many sample, how i can increase resource directly for adapterrmoval process & AdapterRemovalFixPrefix, also for bwa aln, i have seen some example but i am not able to make configure file. i am running currently on slurm and with help of conda. thank you.

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depictio Depictio dashboard for eager: feedback wanted Depictio (open source, from EMBL) turns the output of a workflow run into an interactive dashboard you can share, so nobody has to write a Shiny or Streamlit app for each project. Point a template at any run of a pipeline and you get the same dashboard, which you can edit (UI & YAML), version and comment. 🦴 The eager dashboard template (no account needed) shows endogenous DNA, library complexity, ancient-DNA authentication (damage, fragment length), coverage and genotypes. 🙌 We need your help! Feedback and ideas welcome in #C0AFS06G9HR (all templates and details there) or in the eager GitHub discussion.

Hello! I have a question that is more theoretical than practical. My laboratory has to migrate to an S3 Object Storage system in the (near?) future, so I've been testing eager to work with files saved on an s3 bucket. Here are the version I've tested: • Eager v2 (revision 2.5.1) Nextflow v. 22.10.6 • Eager v3 (dev) Nextflow v. 26.04.7 The aws configuration parameters I used are the same for both tests. What I have noticed is that v2 had troubles with downloading the remote fastqs files: by looking solely at the size, they were 10 times bigger, and they were still compressed! Which created problems as soon as AdapterRemoval started. The error message was: "invalid FASTQ record; sequence/quality length does not match". The v3 (dev) version, instead, works smoothly and the fastq files are downloaded with no problem (yay!) My question is: is this issue related to the Nextflow version, rather than Eager? I've been digging through some old GitHub bug reports about Nextflow and AWS implementation, and it seemed that there were problems up to version 23.09.0 although the problems observed were not too similar to mine. In any case, it seems that our lab will have to migrate to v3 as soon as possible 😄

<!subteam^S016TBDBXHC> Dev meeting has started on WA! play.workadventu.re/@/nf-core/nf-core/office I will try to get the template merged and continue updating the docs

Hi. I am having some doubts about what the % endogenous from endorspy means. From looking at the log, it seems that endorspy is run before removing duplicates. Is this correct, and if so, is there a way to run endorspy only after removing duplicates?

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