# Finished results in specified location (defined with --outdir) .nextflow_log # Log file from Nextflow # Other nextflow hidden files, eg. history of pipeline runs and old logs.","title":"Running the pipeline"},{"location":"usage/#updating-the-pipeline","text":"When you run the above command, Nextflow automatically pulls the pipeline code from GitHub and stores it as a cached version. When running the pipeline after this, it will always use the cached version if available - even if the pipeline has been updated since. To make sure that you're running the latest version of the pipeline, make sure that you regularly update the cached version of the pipeline: nextflow pull dalmolingroup/euryale","title":"Updating the pipeline"},{"location":"usage/#reproducibility","text":"It is a good idea to specify a pipeline version when running the pipeline on your data. This ensures that a specific version of the pipeline code and software are used when you run your pipeline. If you keep using the same tag, you'll be running the same version of the pipeline, even if there have been changes to the code since. First, go to the dalmolingroup/euryale releases page and find the latest pipeline version - numeric only (eg. 1.3.1 ). Then specify this when running the pipeline with -r (one hyphen) - eg. -r 1.3.1 . Of course, you can switch to another version by changing the number after the -r flag. This version number will be logged in reports when you run the pipeline, so that you'll know what you used when you look back in the future. For example, at the bottom of the MultiQC reports.","title":"Reproducibility"},{"location":"usage/#core-nextflow-arguments","text":"NB: These options are part of Nextflow and use a single hyphen (pipeline parameters use a double-hyphen).","title":"Core Nextflow arguments"},{"location":"usage/#-profile","text":"Use this parameter to choose a configuration profile. Profiles can give configuration presets for different compute environments. Several generic profiles are bundled with the pipeline which instruct the pipeline to use software packaged using different methods (Docker, Singularity, Podman, Shifter, Charliecloud, Conda) - see below. We highly recommend the use of Docker or Singularity containers for full pipeline reproducibility, however when this is not possible, Conda is also supported. Note that multiple profiles can be loaded, for example: -profile test,docker - the order of arguments is important! They are loaded in sequence, so later profiles can overwrite earlier profiles. If -profile is not specified, the pipeline will run locally and expect all software to be installed and available on the PATH . This is not recommended, since it can lead to different results on different machines dependent on the computer environment. test A profile with a complete configuration for automated testing Includes links to test data so needs no other parameters other than --outdir docker A generic configuration profile to be used with Docker singularity A generic configuration profile to be used with Singularity podman A generic configuration profile to be used with Podman shifter A generic configuration profile to be used with Shifter charliecloud A generic configuration profile to be used with Charliecloud conda A generic configuration profile to be used with Conda . Please only use Conda as a last resort i.e. when it's not possible to run the pipeline with Docker, Singularity, Podman, Shifter or Charliecloud.","title":"-profile"},{"location":"usage/#-resume","text":"Specify this when restarting a pipeline. Nextflow will use cached results from any pipeline steps where the inputs are the same, continuing from where it got to previously. For input to be considered the same, not only the names must be identical but the files' contents as well. For more info about this parameter, see this blog post . You can also supply a run name to resume a specific run: -resume [run-name] . Use the nextflow log command to show previous run names.","title":"-resume"},{"location":"usage/#-c","text":"Specify the path to a specific config file (this is a core Nextflow command). See the nf-core website documentation for more information.","title":"-c"},{"location":"usage/#custom-configuration","text":"","title":"Custom configuration"},{"location":"usage/#resource-requests","text":"Whilst the default requirements set within the pipeline will hopefully work for most people and with most input data, you may find that you want to customise the compute resources that the pipeline requests. Each step in the pipeline has a default set of requirements for number of CPUs, memory and time. For most of the steps in the pipeline, if the job exits with any of the error codes specified here it will automatically be resubmitted with higher requests (2 x original, then 3 x original). If it still fails after the third attempt then the pipeline execution is stopped. For example, if the pipeline is failing after multiple re-submissions of the DIAMOND_BLASTX process due to an exit code of 137 this would indicate that there is an out of memory issue: [62/149eb0] NOTE: Process `EURYALE:ALIGNMENT:DIAMOND_BLASTX (WT_REP1)` terminated with an error exit status (137) -- Execution is retried (1) Error executing process > 'EURYALE:ALIGNMENT:DIAMOND_BLASTX (WT_REP1)' Caused by: Process `EURYALE:ALIGNMENT:DIAMOND_BLASTX (WT_REP1)` terminated with an error exit status (137) Command executed: diamond \\ blastx \\ --threads 2 \\ --db $DB \\ --query test_minigut_sample2.fasta \\ --outfmt 6 qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore \\ --more-sensitive --top 3 --compress 1 \\ --out test_minigut_sample2.txt \\ --log Command exit status: 137 Command output: (empty) Command error: .command.sh: line 9: 30 Killed Work dir: /home/pipelinetest/work/9d/172ca5881234073e8d76f2a19c88fb Tip: you can replicate the issue by changing to the process work dir and entering the command `bash .command.run`","title":"Resource requests"},{"location":"usage/#for-beginners","text":"A first step to bypass this error, you could try to increase the amount of CPUs, memory, and time for the whole pipeline. Therefore you can try to increase the resource for the parameters --max_cpus , --max_memory , and --max_time . Based on the error above, you have to increase the amount of memory. Therefore you can go to the parameter documentation of rnaseq and scroll down to the show hidden parameter button to get the default value for --max_memory . In this case 128GB, you than can try to run your pipeline again with --max_memory 200GB -resume to skip all process, that were already calculated. If you can not increase the resource of the complete pipeline, you can try to adapt the resource for a single process as mentioned below.","title":"For beginners"},{"location":"usage/#advanced-option-on-process-level","text":"To bypass this error you would need to find exactly which resources are set by the DIAMOND_BLASTX process. The quickest way is to search for process DIAMOND_BLASTX in the dalmolingroup/euryale Github repo . We have standardised the structure of Nextflow DSL2 pipelines such that all module files will be present in the modules/ directory and so, based on the search results, the file we want is modules/nf-core/diamond/blastx/main.nf . If you click on the link to that file you will notice that there is a label directive at the top of the module that is set to label process_high . The Nextflow label directive allows us to organise workflow processes in separate groups which can be referenced in a configuration file to select and configure subset of processes having similar computing requirements. The default values for the process_high label are set in the pipeline's base.config which in this case is defined as 72GB. Providing you haven't set any other standard nf-core parameters to cap the maximum resources used by the pipeline then we can try and bypass the DIAMOND_BLASTX process failure by creating a custom config file that sets at least 72GB of memory, in this case increased to 300GB. The custom config below can then be provided to the pipeline via the -c parameter as highlighted in previous sections. process { withName: 'EURYALE:ALIGNMENT:DIAMOND_BLASTX' { memory = 300.GB } } NB: We specify the full process name i.e. EURYALE:ALIGNMENT:DIAMOND_BLASTX in the config file because this takes priority over the short name ( DIAMOND_BLASTX ) and allows existing configuration using the full process name to be correctly overridden. If you get a warning suggesting that the process selector isn't recognised check that the process name has been specified correctly.","title":"Advanced option on process level"},{"location":"usage/#updating-containers-advanced-users","text":"The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. If for some reason you need to use a different version of a particular tool with the pipeline then you just need to identify the process name and override the Nextflow container definition for that process using the withName declaration. For example, in the dalmolingroup/euryale pipeline a tool called Kraken2 is being used. You can override the default container used by the pipeline by creating a custom config file and passing it as a command-line argument via -c custom.config . Check the default version used by the pipeline in the module file for Kraken2 Find the latest version of the Biocontainer available on Quay.io Create the custom config accordingly: For Docker: nextflow process { withName: KRAKEN2 { container = 'quay.io/biocontainers/kraken2:2.1.3--pl5321hdcf5f25_2' } } For Singularity: nextflow process { withName: KRAKEN2 { container = 'https://depot.galaxyproject.org/singularity/kraken2%3A2.1.3--pl5321hdcf5f25_2' } } For Conda: nextflow process { withName: PANGOLIN { conda = 'bioconda::kraken2=2.1.3' } } NB: If you wish to periodically update individual tool-specific results (e.g. Kraken2) generated by the pipeline then you must ensure to keep the work/ directory otherwise the -resume ability of the pipeline will be compromised and it will restart from scratch.","title":"Updating containers (advanced users)"},{"location":"usage/#running-in-the-background","text":"Nextflow handles job submissions and supervises the running jobs. The Nextflow process must run until the pipeline is finished. The Nextflow -bg flag launches Nextflow in the background, detached from your terminal so that the workflow does not stop if you log out of your session. The logs are saved to a file. Alternatively, you can use screen / tmux or similar tool to create a detached session which you can log back into at a later time. Some HPC setups also allow you to run nextflow within a cluster job submitted your job scheduler (from where it submits more jobs).","title":"Running in the background"},{"location":"usage/#nextflow-memory-requirements","text":"In some cases, the Nextflow Java virtual machines can start to request a large amount of memory. We recommend adding the following line to your environment to limit this (typically in ~/.bashrc or ~./bash_profile ): NXF_OPTS='-Xms1g -Xmx4g'","title":"Nextflow memory requirements"}]}
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diff --git a/sitemap.xml.gz b/sitemap.xml.gz
index 482a3ee64cb094aa4c1ed664bae75644f542fbff..cdf8b45927f49a968c3db9f354f6cde163435700 100644
GIT binary patch
delta 13
Ucmb=gXP58h;AnUlGLgLk03JXDg#Z8m
delta 13
Ucmb=gXP58h;9&6bo5)@P02nm`XaE2J
diff --git a/usage/index.html b/usage/index.html
index 52143d3..709390f 100644
--- a/usage/index.html
+++ b/usage/index.html
@@ -214,7 +214,7 @@ -profile
Note that multiple profiles can be loaded, for example: -profile test,docker - the order of arguments is important!
They are loaded in sequence, so later profiles can overwrite earlier profiles.
-If -profile is not specified, the pipeline will run locally and expect all software to be installed and available on the PATH. This is not recommended, since it can lead to different results on different machines dependent on the computer enviroment.
+If -profile is not specified, the pipeline will run locally and expect all software to be installed and available on the PATH. This is not recommended, since it can lead to different results on different machines dependent on the computer environment.
test- A profile with a complete configuration for automated testing
@@ -272,7 +272,7 @@ Resource requests
Tip: you can replicate the issue by changing to the process work dir and entering the command `bash .command.run`
For beginners
-A first step to bypass this error, you could try to increase the amount of CPUs, memory, and time for the whole pipeline. Therefor you can try to increase the resource for the parameters --max_cpus, --max_memory, and --max_time. Based on the error above, you have to increase the amount of memory. Therefore you can go to the parameter documentation of rnaseq and scroll down to the show hidden parameter button to get the default value for --max_memory. In this case 128GB, you than can try to run your pipeline again with --max_memory 200GB -resume to skip all process, that were already calculated. If you can not increase the resource of the complete pipeline, you can try to adapt the resource for a single process as mentioned below.
+A first step to bypass this error, you could try to increase the amount of CPUs, memory, and time for the whole pipeline. Therefore you can try to increase the resource for the parameters --max_cpus, --max_memory, and --max_time. Based on the error above, you have to increase the amount of memory. Therefore you can go to the parameter documentation of rnaseq and scroll down to the show hidden parameter button to get the default value for --max_memory. In this case 128GB, you than can try to run your pipeline again with --max_memory 200GB -resume to skip all process, that were already calculated. If you can not increase the resource of the complete pipeline, you can try to adapt the resource for a single process as mentioned below.
Advanced option on process level
To bypass this error you would need to find exactly which resources are set by the DIAMOND_BLASTX process. The quickest way is to search for process DIAMOND_BLASTX in the dalmolingroup/euryale Github repo.
We have standardised the structure of Nextflow DSL2 pipelines such that all module files will be present in the modules/ directory and so, based on the search results, the file we want is modules/nf-core/diamond/blastx/main.nf.