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# nf-core/configs: Eddie Configuration
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nf-core pipelines sarek, rnaseq, and atacseq have all been tested on the University of Edinburgh Eddie HPC.
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## Getting help
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There is a Slack channel dedicated to eddie users on the MRC IGMM Slack: [https://igmm.slack.com/channels/eddie3](https://igmm.slack.com/channels/eddie3)
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## Using the Eddie config profile
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To use, run the pipeline with `-profile eddie` (one hyphen).
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This will download and launch the [`eddie.config`](../conf/eddie.config) which has been pre-configured with a setup suitable for the [University of Edinburgh Eddie HPC](https://www.ed.ac.uk/information-services/research-support/research-computing/ecdf/high-performance-computing).
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The configuration file supports running nf-core pipelines with either a Conda environment or Docker containers running under Singularity.
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```bash
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nextflow run nf-core/PIPELINE -profile eddie # ..rest of pipeline flags
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```
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Before running the pipeline you will need to install Nextflow or load it from the module system. Generally the most recent version will be the one you want.
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To list versions:
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```bash
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module avail igmm/apps/nextflow
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```
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To load the most recent version:
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```bash
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module load igmm/apps/nextflow
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```
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This config enables Nextflow to manage the pipeline jobs via the SGE job scheduler and using Conda or Singularity for software management.
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To set up Nextflow on a login node ... TODO
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## Using iGenomes references
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A local copy of the iGenomes resource has been made available on the Eddie HPC so you should be able to run the pipeline against any reference available in the `igenomes.config`.
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You can do this by simply using the `--genome <GENOME_ID>` parameter.
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## Adjusting maximum resources
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This config is set for IGMM standard nodes which have 32 cores and 384GB memory. If you are a non-IGMM user, please see the [ECDF specification](https://www.wiki.ed.ac.uk/display/ResearchServices/Memory+Specification) and adjust the `--clusterOptions` flag appropriately, e.g.
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```bash
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--clusterOptions "-C mem256GB" --max_memory "256GB"
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```
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