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Template update for nf-core/tools version 2.0
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root = true | ||
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[*] | ||
charset = utf-8 | ||
end_of_line = lf | ||
insert_final_newline = true | ||
trim_trailing_whitespace = true | ||
indent_size = 4 | ||
indent_style = space | ||
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[*.{yml,yaml}] | ||
indent_size = 2 | ||
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# These files are edited and tested upstream in nf-core/modules | ||
[/modules/nf-core/**] | ||
charset = unset | ||
end_of_line = unset | ||
insert_final_newline = unset | ||
trim_trailing_whitespace = unset | ||
indent_style = unset | ||
indent_size = unset | ||
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[/assets/email*] | ||
indent_size = unset |
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name: nf-core AWS full size tests | ||
# This workflow is triggered on published releases. | ||
# It can be additionally triggered manually with GitHub actions workflow dispatch. | ||
# It can be additionally triggered manually with GitHub actions workflow dispatch button. | ||
# It runs the -profile 'test_full' on AWS batch | ||
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on: | ||
workflow_run: | ||
workflows: ["nf-core Docker push (release)"] | ||
types: [completed] | ||
release: | ||
types: [published] | ||
workflow_dispatch: | ||
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env: | ||
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }} | ||
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }} | ||
TOWER_ACCESS_TOKEN: ${{ secrets.AWS_TOWER_TOKEN }} | ||
AWS_JOB_DEFINITION: ${{ secrets.AWS_JOB_DEFINITION }} | ||
AWS_JOB_QUEUE: ${{ secrets.AWS_JOB_QUEUE }} | ||
AWS_S3_BUCKET: ${{ secrets.AWS_S3_BUCKET }} | ||
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jobs: | ||
run-awstest: | ||
run-tower: | ||
name: Run AWS full tests | ||
if: github.repository == 'nf-core/epitopeprediction' | ||
runs-on: ubuntu-latest | ||
steps: | ||
- name: Setup Miniconda | ||
uses: conda-incubator/setup-miniconda@v2 | ||
with: | ||
auto-update-conda: true | ||
python-version: 3.7 | ||
- name: Install awscli | ||
run: conda install -c conda-forge awscli | ||
- name: Start AWS batch job | ||
- name: Launch workflow via tower | ||
uses: nf-core/tower-action@master | ||
# TODO nf-core: You can customise AWS full pipeline tests as required | ||
# Add full size test data (but still relatively small datasets for few samples) | ||
# on the `test_full.config` test runs with only one set of parameters | ||
# Then specify `-profile test_full` instead of `-profile test` on the AWS batch command | ||
run: | | ||
aws batch submit-job \ | ||
--region eu-west-1 \ | ||
--job-name nf-core-epitopeprediction \ | ||
--job-queue $AWS_JOB_QUEUE \ | ||
--job-definition $AWS_JOB_DEFINITION \ | ||
--container-overrides '{"command": ["nf-core/epitopeprediction", "-r '"${GITHUB_SHA}"' -profile test --outdir s3://'"${AWS_S3_BUCKET}"'/epitopeprediction/results-'"${GITHUB_SHA}"' -w s3://'"${AWS_S3_BUCKET}"'/epitopeprediction/work-'"${GITHUB_SHA}"' -with-tower"], "environment": [{"name": "TOWER_ACCESS_TOKEN", "value": "'"$TOWER_ACCESS_TOKEN"'"}]}' | ||
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with: | ||
workspace_id: ${{ secrets.TOWER_WORKSPACE_ID }} | ||
bearer_token: ${{ secrets.TOWER_BEARER_TOKEN }} | ||
compute_env: ${{ secrets.TOWER_COMPUTE_ENV }} | ||
pipeline: ${{ github.repository }} | ||
revision: ${{ github.sha }} | ||
workdir: s3://${{ secrets.AWS_S3_BUCKET }}/work/epitopeprediction/work-${{ github.sha }} | ||
parameters: | | ||
{ | ||
"outdir": "s3://${{ secrets.AWS_S3_BUCKET }}/epitopeprediction/results-${{ github.sha }}" | ||
} | ||
profiles: '[ "test_full", "aws_tower" ]' | ||
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name: nf-core AWS test | ||
# This workflow is triggered on push to the master branch. | ||
# It can be additionally triggered manually with GitHub actions workflow dispatch. | ||
# It runs the -profile 'test' on AWS batch. | ||
# This workflow can be triggered manually with the GitHub actions workflow dispatch button. | ||
# It runs the -profile 'test' on AWS batch | ||
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on: | ||
workflow_dispatch: | ||
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||
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||
env: | ||
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }} | ||
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }} | ||
TOWER_ACCESS_TOKEN: ${{ secrets.AWS_TOWER_TOKEN }} | ||
AWS_JOB_DEFINITION: ${{ secrets.AWS_JOB_DEFINITION }} | ||
AWS_JOB_QUEUE: ${{ secrets.AWS_JOB_QUEUE }} | ||
AWS_S3_BUCKET: ${{ secrets.AWS_S3_BUCKET }} | ||
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||
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jobs: | ||
run-awstest: | ||
run-tower: | ||
name: Run AWS tests | ||
if: github.repository == 'nf-core/epitopeprediction' | ||
runs-on: ubuntu-latest | ||
steps: | ||
- name: Setup Miniconda | ||
uses: conda-incubator/setup-miniconda@v2 | ||
- name: Launch workflow via tower | ||
uses: nf-core/tower-action@master | ||
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||
with: | ||
auto-update-conda: true | ||
python-version: 3.7 | ||
- name: Install awscli | ||
run: conda install -c conda-forge awscli | ||
- name: Start AWS batch job | ||
# TODO nf-core: You can customise CI pipeline run tests as required | ||
# For example: adding multiple test runs with different parameters | ||
# Remember that you can parallelise this by using strategy.matrix | ||
run: | | ||
aws batch submit-job \ | ||
--region eu-west-1 \ | ||
--job-name nf-core-epitopeprediction \ | ||
--job-queue $AWS_JOB_QUEUE \ | ||
--job-definition $AWS_JOB_DEFINITION \ | ||
--container-overrides '{"command": ["nf-core/epitopeprediction", "-r '"${GITHUB_SHA}"' -profile test --outdir s3://'"${AWS_S3_BUCKET}"'/epitopeprediction/results-'"${GITHUB_SHA}"' -w s3://'"${AWS_S3_BUCKET}"'/epitopeprediction/work-'"${GITHUB_SHA}"' -with-tower"], "environment": [{"name": "TOWER_ACCESS_TOKEN", "value": "'"$TOWER_ACCESS_TOKEN"'"}]}' | ||
workspace_id: ${{ secrets.TOWER_WORKSPACE_ID }} | ||
bearer_token: ${{ secrets.TOWER_BEARER_TOKEN }} | ||
compute_env: ${{ secrets.TOWER_COMPUTE_ENV }} | ||
pipeline: ${{ github.repository }} | ||
revision: ${{ github.sha }} | ||
workdir: s3://${{ secrets.AWS_S3_BUCKET }}/work/epitopeprediction/work-${{ github.sha }} | ||
parameters: | | ||
{ | ||
"outdir": "s3://${{ secrets.AWS_S3_BUCKET }}/epitopeprediction/results-${{ github.sha }}" | ||
} | ||
profiles: '[ "test", "aws_tower" ]' | ||
|
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@@ -3,7 +3,6 @@ work/ | |
data/ | ||
results/ | ||
.DS_Store | ||
tests/ | ||
testing/ | ||
testing* | ||
*.pyc |
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# nf-core/epitopeprediction: Citations | ||
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## [nf-core](https://pubmed.ncbi.nlm.nih.gov/32055031/) | ||
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> Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Mar;38(3):276-278. doi: 10.1038/s41587-020-0439-x. PubMed PMID: 32055031. | ||
## [Nextflow](https://pubmed.ncbi.nlm.nih.gov/28398311/) | ||
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> Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 28398311. | ||
## Pipeline tools | ||
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* [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) | ||
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* [MultiQC](https://www.ncbi.nlm.nih.gov/pubmed/27312411/) | ||
> Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924. | ||
## Software packaging/containerisation tools | ||
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* [Anaconda](https://anaconda.com) | ||
> Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web. | ||
* [Bioconda](https://pubmed.ncbi.nlm.nih.gov/29967506/) | ||
> Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018 Jul;15(7):475-476. doi: 10.1038/s41592-018-0046-7. PubMed PMID: 29967506. | ||
* [BioContainers](https://pubmed.ncbi.nlm.nih.gov/28379341/) | ||
> da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-Riverol Y. BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics. 2017 Aug 15;33(16):2580-2582. doi: 10.1093/bioinformatics/btx192. PubMed PMID: 28379341; PubMed Central PMCID: PMC5870671. | ||
* [Docker](https://dl.acm.org/doi/10.5555/2600239.2600241) | ||
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* [Singularity](https://pubmed.ncbi.nlm.nih.gov/28494014/) | ||
> Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; PubMed Central PMCID: PMC5426675. |
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