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Update content processing for new website (#848)
* parse metadata in new format * typo # ci skip * ignore workdir * remove selectively * temp * bugfix # ci skip * fix ref # ci skip * more temp # ci skip * don't remove tasks # ci skip # publish * pretty print # ci skip # publish * move get_sha to utils * add get_sha to workflow_utils * push meta to experimental website * monitor separate;y * don't build images for website * id -> task_id * add description if missing * only publish explicitly * test website # publish * fix ref # publish * untemp * remove patch # publish * clean up readmes # publish * also publish the bib * remove experimental website repo * remove unnecessary diff * add code url to function metadata # publish * set base to main # publish * code_url was already taken # publish
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.github/workflows/run_tests.yml

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if: |
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!endsWith(github.event.head_commit.message, '# ci skip') &&
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!startsWith(github.ref, 'refs/heads/test_process') &&
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!startsWith(github.ref, 'refs/heads/test_website') &&
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(
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(github.event_name != 'pull_request_review') ||
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(

.github/workflows/update_website_content.yml

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with:
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fetch-depth: 1
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repository: openproblems-bio/website
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ref: main
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path: website
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token: ${{ secrets.GH_ACTIONS_WEBSITE_PAT }}
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pip install -U --editable ./openproblems[process]
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python -c "import openproblems"
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- name: Parse results
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- name: Parse metadata
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run: |
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rm -r website/content/benchmarks/*/
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python openproblems/workflow/generate_website_markdown.py website/content/benchmarks
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cp openproblems/main.bib website/static/bibliography
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python openproblems/workflow/parse_metadata.py website/results
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cp openproblems/main.bib website/bibliography/library.bib
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cd website
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git diff --exit-code --quiet || echo "CHANGED=true" >> $GITHUB_ENV
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- name: Upload markdown
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- name: Upload json
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uses: actions/upload-artifact@main
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with:
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name: markdown
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name: json
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path: website/content/benchmarks
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- name: Push to openproblems-bio/website
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)
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uses: peter-evans/create-pull-request@v4
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with:
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base: main
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branch: ${{ env.UPDATE_BRANCH_NAME }}
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delete-branch: true
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base: main
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title: '[auto] Update benchmark content'
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reviewers: scottgigante-immunai,rcannood,dburkhardt
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reviewers: scottgigante-immunai,rcannood
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path: './website'
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token: ${{ secrets.GH_ACTIONS_WEBSITE_PAT }}
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author: "openproblems-bio <singlecellopenproblems@protonmail.com>"

main.bib

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author = {Patrick Schober and Christa Boer and Lothar A. Schwarte},
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year = {2018},
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month = may,
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journal = {Anesthesia {\&}amp$\mathsemicolon$ Analgesia},
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journal = {Anesthesia {\&} Analgesia},
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publisher = {Ovid Technologies (Wolters Kluwer Health)},
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volume = {126},
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number = {5},

openproblems/tasks/_batch_integration/batch_integration_embed/README.md

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<!--- TODO: add links --->
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# Batch integration embedding
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## The task
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This is a sub-task of the overall batch integration task. Batch (or data) integration
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integrates datasets across batches that arise from various biological and technical
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sources. Methods that integrate batches typically have three different types of output:

openproblems/tasks/_batch_integration/batch_integration_feature/README.md

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<!--- TODO: add links --->
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# Batch integration feature
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## The task
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This is a sub-task of the overall batch integration task. Batch (or data) integration
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integrates datasets across batches that arise from various biological and technical
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sources. Methods that integrate batches typically have three different types of output:

openproblems/tasks/_batch_integration/batch_integration_graph/README.md

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<!--- TODO: add links --->
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# Batch integration (graph)
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## The task
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This is a sub-task of the overall batch integration task. Batch (or data) integration
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methods integrate datasets across batches that arise from various biological and
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technical sources. Methods that integrate batches typically have three different types

openproblems/tasks/_cell_cell_communication/README.md

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# Cell-cell Communication
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## The task
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The growing availability of single-cell data has sparked an increased
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interest in the inference of cell-cell communication (CCC),
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with an ever-growing number of computational tools developed for this purpose.

openproblems/tasks/_cell_cell_communication/cell_cell_communication_ligand_target/README.md

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# Cell-cell Communication
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## The task
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# Cell-cell Communication (ligand-target)
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The growing availability of single-cell data has sparked an increased
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interest in the inference of cell-cell communication (CCC),

openproblems/tasks/_cell_cell_communication/cell_cell_communication_source_target/README.md

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# Cell-cell Communication
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## The task
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# Cell-cell Communication (source-target)
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The growing availability of single-cell data has sparked an increased
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interest in the inference of cell-cell communication (CCC),

openproblems/tasks/denoising/README.md

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# Denoising
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## The task
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Single-cell RNA-Seq protocols only detect a fraction of the mRNA molecules present
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in each cell. As a result, the measurements (UMI counts) observed for each gene and each
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cell are associated with generally high levels of technical noise ([Grün et al.,

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