operon
AI-powered IDE for bioinformatics — built by biologists, for biologists
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- hooks.json
- ci.yml
- docs.yml
- release.yml
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- A530A30F4A4B6D2B0563C6ACD7D47E4B
- B5D63EBC8A9809828BCAFA8911C83C80
- state.mpack
- CodeChunks.db
- SemanticSymbols.db
- CodeChunks.db
- SemanticSymbols.db
- 3b2e4196-12a4-4363-b745-8690a6f73a8c
- 02ce1b0c-f26c-4df7-b662-0df214749e6b.vsidx
- 44fb1343-e2ed-4733-bb0f-9b02e45be6b9.vsidx
- 777e557a-cc13-449d-afb0-1f2ee651ac7c.vsidx
- 91ddadb2-1b36-4832-8fe0-ac573110e6ea.vsidx
- a54d3ec4-85ee-43ed-9d2a-24583917bd1c.vsidx
- .wsuo
- DocumentLayout.backup.json
- DocumentLayout.json
- ProjectSettings.json
- slnx.sqlite
- VSWorkspaceState.json
- sign.png
- icon.json
- site.css
- site.js
- plan-mode-data-audit.md
- ai-modes-dropdown.png
- auth-authorize.png
- auth-authorize2.png
- auth-code.png
- auth-oauth.png
- auth-paste-code.png
- auth-selection.png
- auth-theme.png
- auth-waiting.png
- auth-welcome-art.png
- file-explorer.png
- git-panel.png
- help-panel.png
- install-dmg.png
- install-security.png
- Logo-icon-01.png
- Logo-icon_Final.png
- main-workspace.png
- operon_poster.png
- protocol-generate.png
- protocol-manual.png
- protocols-list.png
- protocols1.png
- protocols2.png
- protocols3.png
- pubmed-toggle.png
- settings-panel.png
- setup-claude-done.png
- setup-claude.png
- setup-tools-done.png
- setup-tools-progress.png
- setup-tools.png
- setup-welcome.png
- setup-xcode-dialog.png
- setup-xcode-done.png
- setup-xcode-download.png
- setup-xcode-license.png
- setup-xcode-progress.png
- setup-xcode.png
- ssh-connect.png
- tour-ai-modes.png
- tour-biologists.png
- tour-hpc.png
- tour-shortcuts.png
- tour-workspace.png
- 01_macos_installation.png
- 02_remote_server_connection.png
- 03_claude_remote_install.png
- 04_scanpy_scRNAseq.png
- 05_cellpose_segmentation.png
- generate_thumbnails.py
- change-record-2026-08-13-watchdog-removal.md
- download.html
- downloads.json
- guide.html
- hpc.html
- index.html
- mcp.html
- methods_section.md
- operon_architecture_fig1.svg
- private-llm.html
- protocols.html
- sandboxed-data-mount-spec.md
- tutorials.html
- workshop.html
- workshop_archive.html
- index.md
- mcp.md
- modes.md
- private-llm.md
- providers.md
- pubmed.md
- extra.css
- architecture.md
- gotchas.md
- index.md
- slurm.md
- ssh.md
- tmux.md
- build-from-source.md
- index.md
- linux.md
- macos.md
- windows.md
- browse.md
- custom.md
- index.md
- atacseq.md
- bulk-rnaseq-deseq2.md
- index.md
- pubmed-review.md
- scrna-pbmc.md
- spatial-visium.md
- code-editor.md
- file-explorer.md
- git.md
- index.md
- settings.md
- shortcuts.md
- terminal.md
- theme.md
- architecture.md
- changelog.md
- contributing.md
- faq.md
- img
- index.md
- quickstart.md
- troubleshooting.md
- mkdocs.yml
- portkey.json
- agent_d.py
- prompt.md
- README.md
- SKILL.md
- multimer.md
- SKILL.md
- api_reference.md
- SKILL.md
- diff_splicing_leafcutter.R
- diff_splicing_rmats.sh
- SKILL.md
- usage-guide.md
- isoform_switch_analysis.R
- SKILL.md
- usage-guide.md
- longread_splicing_pipeline.sh
- SKILL.md
- usage-guide.md
- fraser2_rare_disease.R
- SKILL.md
- usage-guide.md
- plot_sashimi.py
- SKILL.md
- usage-guide.md
- sc_splicing_brie2.py
- SKILL.md
- usage-guide.md
- spliceai_clingen_classify.py
- SKILL.md
- usage-guide.md
- splicing_qc.py
- SKILL.md
- usage-guide.md
- quantify_splicing.py
- SKILL.md
- usage-guide.md
- best_practices.md
- concatenation.md
- data_structure.md
- io_operations.md
- manipulation.md
- SKILL.md
- covabdab_gen_curation_allBinders_allVariants_v2_24-03-12.ipynb
- NTD_SA.npy
- RBD_SA.npy
- crowe_ebola_processing_24-03-07.ipynb
- denovo_trastuzamab_24-02-29.ipynb
- detagging_script_24-03-04.ipynb
- final_concat_v2_24-03-12.ipynb
- wang_preprint_flu_cleaning_24-01-03.ipynb
- 10618_antigen_alignment_v1_24-03-06.ipynb
- AA_10618_LLM-clean_24-03-06.ipynb
- detagging_script_24-03-04.ipynb
- SAbDab_final_clean_v1_24-03-04.ipynb
- detagging_nonSAbDab_24-03-12.ipynb
- signalP_summary_output_24-03-12.txt
- atlas_antigen_alignment_v1_24-03-04.ipynb
- published_LIBRA-seq_concatenation_24-05-31.ipynb
- ebola_Bornholdt_24-03-07.ipynb
- ebola_EhrHardt_24-01-03.ipynb
- gilman_RSV_24-01-04.ipynb
- hcv_24-01-03.ipynb
- zurbuchen_data_23-03-08.ipynb
- ASAb_database_metadata_v2_24-03-12.xlsx
- example_training_data.csv
- full_model_training_24-03-12.py
- selected_abs_Figure_2-3_24-06-10.ipynb
- figure1_plots_24-06-10.ipynb
- output_filtering_annotation.ipynb
- RBD_1K_sequences_24-03-16.csv
- selected_abs_Figure_2-3_24-06-10.ipynb
- selected_abs_for_testing.csv
- selection_pipeline_24-03-16.ipynb
- generate_antibodies.py
- LICENSE
- MAGE_annotated_training_data.zip
- README.md
- README.md
- SKILL.md
- README.md
- SKILL.md
- archr_template.R
- integration.md
- peaks_motifs.md
- build_archr.R
- downstream_archr.R
- SKILL.md
- PROTOCOL.md
- __init__.py
- Biomaster.py
- CheckAgent.py
- Knowledge.py
- ollama.py
- prompts.py
- ToolAgent.py
- utils.py
- README.md
- TruSeq3-PE.fa
- Plan_Knowledge.json
- Task_Knowledge.json
- conf.py
- index.rst
- installation.rst
- introduction.rst
- other.rst
- rag.rst
- usage.rst
- make.bat
- Makefile
- requirements.txt
- example.py
- example.py
- 001_DEBUG_Input_1.json
- 001_DEBUG_Input_2.json
- 001_DEBUG_Input_3.json
- 001_DEBUG_Input_4.json
- 001_DEBUG_Input_5.json
- 001_DEBUG_Output_1.json
- 001_DEBUG_Output_2.json
- 001_DEBUG_Output_3.json
- 001_DEBUG_Output_4.json
- 001_DEBUG_Output_5.json
- 001_PLAN.json
- 001_Step_1.sh
- 001_Step_2.sh
- 001_Step_3.sh
- 001_Step_4.sh
- 001_Step_5.sh
- 003_DEBUG_Input_1.json
- 003_DEBUG_Input_2.json
- 003_DEBUG_Input_3.json
- 003_DEBUG_Input_4.json
- 003_DEBUG_Output_1.json
- 003_DEBUG_Output_2.json
- 003_DEBUG_Output_3.json
- 003_DEBUG_Output_4.json
- 003_PLAN.json
- 003_Step_1.sh
- 003_Step_2.sh
- 003_Step_3.sh
- 003_Step_4.sh
- alignment_stats.sh
- bam2fq.sh
- basecaller.sh
- dorado_sum.sh
- eventalign.sh
- filter.sh
- filtered_plot.sh
- host_removal.sh
- indexbam.sh
- map_fastq2_ref.sh
- methy_iden.sh
- quantififation.sh
- raw_plot.sh
- result_sum.sh
- run-add-hicnormvector-to-mcool.sh
- run-addfrag2pairs.sh
- run-bam2pairs.sh
- run-bwa-mem.sh
- run-cool2multirescool.sh
- run-cooler-balance.sh
- run-cooler.sh
- run-fastqc.sh
- run-juicebox-pre-addnorm.sh
- run-juicebox-pre.sh
- run-juicer.sh
- run-list.sh
- run-merge-pairs.sh
- run-pairs-patch.sh
- run-pairsam-filter.sh
- run-pairsam-markasdup.sh
- run-pairsam-merge.sh
- run-pairsam-parse-sort.sh
- run-pairsqc-merge.sh
- run-pairsqc-single.sh
- run-sort-bam.sh
- Biomaster.svg
- UI.png
- wechat.jpg
- .readthedocs.yaml
- config.yaml
- README.md
- requirements.txt
- run.py
- run.sh
- runv.py
- README.md
- SKILL.md
- api_reference.md
- llm_providers.md
- use_cases.md
- generate_report.py
- setup_environment.py
- SKILL.md
- SKILL.md
- SKILL.md
- protocols.md
- troubleshooting.md
- SKILL.md
- tool-comparison.md
- SKILL.md
- quiz.md
- QUICK_REFERENCE.md
- README.md
- SKILL.md
- SKILL.md
- search
- search.mjs
- SKILL.md
- SKILL.md
- yaml-spec.md
- SKILL.md
- PROTOCOL.md
- PROTOCOL.md
- SKILL.md
- coloc_abf_pipeline.R
- coloc_analysis.R
- coloc_susie.R
- coloc_susie_multicausal.R
- regional_plots.R
- SKILL.md
- usage-guide.md
- magma_genebased.sh
- multi_evidence_integration.R
- SKILL.md
- usage-guide.md
- finemap_pipeline.sh
- pip_visualization.R
- susie_finemapping.R
- susie_rss_finemap.R
- susiex_multiancestry.sh
- SKILL.md
- usage-guide.md
- lava_local_rg.R
- ldsc_crosstrait_rg.sh
- SKILL.md
- usage-guide.md
- genomic_sem_commonfactor.R
- mtag_pipeline.sh
- SKILL.md
- usage-guide.md
- ldak_sumher.sh
- ldsc_partitioned_h2.sh
- SKILL.md
- usage-guide.md
- cmaverse_4way.R
- eqtl_mediation.R
- mvmr_mediation.R
- sensitivity_analysis.R
- SKILL.md
- usage-guide.md
- cis_mr_drug_target.R
- mr_visualization.R
- two_sample_mr.R
- twosamplemr_analysis.R
- SKILL.md
- usage-guide.md
- bidirectional_mr.R
- cause_analysis.R
- mr_presso_analysis.R
- sensitivity_battery.R
- simex_egger_correction.R
- SKILL.md
- usage-guide.md
- cis_pqtl_mr.R
- phewas_drug_target_mr.R
- SKILL.md
- usage-guide.md
- focus_finemap.sh
- s_predixcan_pipeline.sh
- SKILL.md
- usage-guide.md
- SKILL.md
- all.csv
- all_human.csv
- all_human_mixed.csv
- all_mouse.csv
- Azimuth.csv
- BCL.csv
- coloncancer.csv
- HCA.csv
- HCL.csv
- literature.csv
- lungcancer.csv
- MCA.csv
- all.csv
- compiled.csv
- relation.csv
- Gene-Expression-Atlas.png
- README.md
- __init__.py
- config.py
- eval.py
- get_expression_score.py
- get_gene_summary.py
- get_lit_review.py
- get_prediction.py
- get_selection.py
- LLM.py
- utils.py
- top_3.txt
- top_3.txt
- top_3.txt
- top_3.txt
- top_3.txt
- top_3.txt
- top_3.txt
- top_3.txt
- top_3.txt
- merged_top_3_max_None.csv
- top_3_max_None.csv
- top_3_max_None.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_3_max_None.csv
- top_3_max_None.txt
- summary_dict_MCA (deepseek-r1).json
- summary_dict_MCA (o1-mini).json
- summary_dict_MCA (o1-preview).json
- test_gene_summary_augmented.ipynb
- lit_dict_MCA (claude-3.5-sonnet).json
- lit_dict_MCA (deepseek-r1).json
- lit_dict_MCA (o1-mini).json
- lit_dict_MCA (o1-preview).json
- test_lit_review_augmented.ipynb
- comparison.ipynb
- top_3.txt
- top_3.txt
- top_3.txt
- top_3.txt
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- top_3.txt
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- top_3.txt
- top_3.txt
- top_3.txt
- average_scores_grouped_by_manual_CLname_top_2_max_None.json
- average_scores_grouped_by_manual_CLname_top_3_max_None.json
- average_scores_grouped_by_manual_CLname_top_4_max_None.json
- average_scores_grouped_by_manual_CLname_top_5_max_None.json
- cell_wise_violin_plot_data.csv
- combined_plot.pdf
- fig e) different number of cell type candidates.pdf
- line_plot_data.csv
- merged_top_2_max_None.csv
- merged_top_3_max_None copy.csv
- merged_top_3_max_None.csv
- merged_top_4_max_None.csv
- merged_top_5_max_None.csv
- unweighted_average_scores_by_dataset_top_2_max_None.json
- unweighted_average_scores_by_dataset_top_3_max_None.json
- unweighted_average_scores_by_dataset_top_4_max_None.json
- unweighted_average_scores_by_dataset_top_5_max_None.json
- violin_plot_data.csv
- weighted_average_scores_by_dataset_top_2_max_None.json
- weighted_average_scores_by_dataset_top_3_max_None.json
- weighted_average_scores_by_dataset_top_4_max_None.json
- weighted_average_scores_by_dataset_top_5_max_None.json
- all_human_mixed_predictions.csv
- top_3_max_None.csv
- improvement.csv
- test.ipynb
- top_2_max_None.csv
- top_2_max_None.txt
- top_3_max_3.csv
- top_3_max_3.txt
- top_3_max_5.csv
- top_3_max_5.txt
- top_3_max_8.csv
- top_3_max_8.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_4_max_None.csv
- top_4_max_None.txt
- top_5_max_None.csv
- top_5_max_None.txt
- top_2_max_None.csv
- top_2_max_None.txt
- top_3_max_10.txt
- top_3_max_3.csv
- top_3_max_3.txt
- top_3_max_5.csv
- top_3_max_5.txt
- top_3_max_8.csv
- top_3_max_8.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_4_max_None.csv
- top_4_max_None.txt
- top_5_max_None.csv
- top_5_max_None.txt
- top_2_max_None.csv
- top_2_max_None.txt
- top_3_max_10.txt
- top_3_max_3.csv
- top_3_max_3.txt
- top_3_max_5.csv
- top_3_max_5.txt
- top_3_max_8.csv
- top_3_max_8.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_4_max_None.csv
- top_4_max_None.txt
- top_5_max_None.csv
- top_5_max_None.txt
- cellxgene_top_1.txt
- improvement.csv
- rerank_2_top_1.txt
- rerank_2_top_2.txt
- rerank_3_top_1.txt
- rerank_3_top_1_new.txt
- rerank_3_top_3.txt
- test.ipynb
- top_2_max_None.csv
- top_2_max_None.txt
- top_3.csv
- top_3_max_3.csv
- top_3_max_3.txt
- top_3_max_5.csv
- top_3_max_5.txt
- top_3_max_8.csv
- top_3_max_8.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_4_max_None.csv
- top_4_max_None.txt
- top_5_max_None.csv
- top_5_max_None.txt
- top_2_max_None.csv
- top_2_max_None.txt
- top_3_max_3.csv
- top_3_max_3.txt
- top_3_max_5.csv
- top_3_max_5.txt
- top_3_max_8.csv
- top_3_max_8.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_4_max_None.csv
- top_4_max_None.txt
- top_5_max_None.csv
- top_5_max_None.txt
- top_2_max_None.csv
- top_2_max_None.txt
- top_3_max_3.csv
- top_3_max_3.txt
- top_3_max_5.csv
- top_3_max_5.txt
- top_3_max_8.csv
- top_3_max_8.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_4_max_None.csv
- top_4_max_None.txt
- top_5.txt
- top_5_max_None.csv
- top_5_max_None.txt
- top_2_max_None.csv
- top_2_max_None.txt
- top_3_max_10.txt
- top_3_max_3.csv
- top_3_max_3.txt
- top_3_max_5.csv
- top_3_max_5.txt
- top_3_max_8.csv
- top_3_max_8.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_4_max_None.csv
- top_4_max_None.txt
- top_5_max_None.csv
- top_5_max_None.txt
- given_potential_cell_types copy.txt
- given_potential_cell_types.txt
- rerank_3_top_1.txt
- rerank_3_top_3.txt
- top_2_max_None.csv
- top_2_max_None.txt
- top_3_(num).txt
- top_3_max_3.csv
- top_3_max_3.txt
- top_3_max_5.csv
- top_3_max_5.txt
- top_3_max_8.csv
- top_3_max_8.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_4_max_None.csv
- top_4_max_None.txt
- top_5_max_None.csv
- top_5_max_None.txt
- top_5_rerank.txt
- improvement.csv
- test.ipynb
- top_2_max_None.csv
- top_2_max_None.txt
- top_3_max_3.csv
- top_3_max_3.txt
- top_3_max_5.csv
- top_3_max_5.txt
- top_3_max_8.csv
- top_3_max_8.txt
- top_3_max_None.csv
- top_3_max_None.txt
- top_4_max_None.csv
- top_4_max_None.txt
- top_5_max_None.csv
- top_5_max_None.txt
- a) Results table like f2d in GPTCellType (processed).pdf
- b) Average agreement score on all datasets accross different base models (processed).pdf
- c) Why CellxGene itself can't work & Why our workflow can work (processed).pdf
- d) Illustration - Additional domain knowledge actually hurts the performance (processed).pdf
- d) Result - Additional domain knowledge actually hurts the performance (processed).pdf
- e) Effect of # of cell type candidates predicted (processed).pdf
- f) Effect of # of given marker genes in the prompt (processed).pdf
- Fig_a - Results table like f2d in GPTCellType.ipynb
- Fig_b - Average agreement score on all datasets accross different base models.ipynb
- Fig_e Effect of # of cell type candidates predicted.ipynb
- Fig_f - Effect of # of given marker genes in the prompt.ipynb
- Fig_g - Given mixed marker genes, to predict the mixed cell types.ipynb
- g) Given mixed marker genes, to predict the mixed cell types (processed).pdf
- .gitattributes
- .gitignore
- README.md
- requirements.txt
- README.md
- SKILL.md
- cellbender_template.sh
- diagnostics.md
- cellbender_slurm.sh
- load_into_scanpy.py
- run_cellbender.sh
- SKILL.md
- cellchat_template.R
- multi_dataset_comparison.md
- plotting_guide.md
- single_dataset.md
- build_cellchat.R
- compare_cellchat.R
- SKILL.md
- SKILL.md
- SKILL.md
- api-reference.md
- SKILL.md
- SKILL.md
- SKILL.md
- search
- search.mjs
- SKILL.md
- chem_tools.py
- README.md
- SKILL.md
- molecular_tools.py
- README.md
- SKILL.md
- quiz.md
- QUICK_REFERENCE.md
- README.md
- SKILL.md
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- SKILL.md
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- methylkit_analysis.R
- SKILL.md
- usage-guide.md
- dada2_workflow.R
- SKILL.md
- usage-guide.md
- SKILL.md
- aldex2_analysis.R
- SKILL.md
- usage-guide.md
- diversity_analysis.R
- SKILL.md
- usage-guide.md
- run_picrust2.sh
- SKILL.md
- usage-guide.md
- qiime2_16s.sh
- SKILL.md
- usage-guide.md
- assign_silva.R
- SKILL.md
- usage-guide.md
- coping-exercises.md
- mat-medications.md
- SKILL.md
- SKILL.md
- evolution_agent.py
- SKILL.md
- skill.yaml
- mrvi_template.py
- run_mrvi.py
- SKILL.md
- harmonize_data.R
- SKILL.md
- usage-guide.md
- diablo_workflow.R
- SKILL.md
- usage-guide.md
- mofa_workflow.R
- SKILL.md
- usage-guide.md
- snf_clustering.R
- SKILL.md
- usage-guide.md
- multimodal_agent.py
- SKILL.md
- SKILL.md
- SKILL.md
- SKILL.md
- SKILL.md
- SKILL.md
- visualization_gsea.R
- visualization_ora.R
- SKILL.md
- usage-guide.md
- go_all_ontologies.R
- go_enrichment_basic.R
- SKILL.md
- usage-guide.md
- gsea_go.R
- gsea_msigdb.R
- SKILL.md
- usage-guide.md
- kegg_enrichment.R
- kegg_module.R
- SKILL.md
- usage-guide.md
- reactome_gsea.R
- reactome_ora.R
- SKILL.md
- usage-guide.md
- wikipathways_explore.R
- wikipathways_ora.R
- SKILL.md
- usage-guide.md
- _meta.json
- SKILL.md
- SKILL.md
- run_beagle_imputation.sh
- SKILL.md
- usage-guide.md
- run_shapeit.sh
- SKILL.md
- usage-guide.md
- imputation_qc.py
- SKILL.md
- usage-guide.md
- download_reference.sh
- SKILL.md
- usage-guide.md
- gwas_pipeline.sh
- SKILL.md
- usage-guide.md
- ld_analysis.sh
- SKILL.md
- usage-guide.md
- qc_pipeline.sh
- SKILL.md
- usage-guide.md
- structure_analysis.sh
- SKILL.md
- usage-guide.md
- basic_analysis.py
- SKILL.md
- usage-guide.md
- selection_scan.py
- SKILL.md
- usage-guide.md
- README.md
- SKILL.md
- primer_design.py
- SKILL.md
- usage-guide.md
- validate_primers.py
- SKILL.md
- usage-guide.md
- qpcr_design.py
- SKILL.md
- usage-guide.md
- qc-checklist.md
- standard-pipeline.md
- SKILL.md
- binding-qc.md
- composite-scoring.md
- expression-qc.md
- structural-qc.md
- SKILL.md
- esmfold_client.py
- README.md
- SKILL.md
- temperature-guide.md
- SKILL.md
- load_maxquant.py
- SKILL.md
- usage-guide.md
- diann_analysis.sh
- SKILL.md
- usage-guide.md
- differential_abundance.py
- limma_analysis.R
- SKILL.md
- usage-guide.md
- fdr_filtering.py
- SKILL.md
- usage-guide.md
- protein_groups.py
- SKILL.md
- usage-guide.md
- qc_analysis.py
- SKILL.md
- usage-guide.md
- phospho_analysis.py
- SKILL.md
- usage-guide.md
- lfq_normalization.py
- SKILL.md
- usage-guide.md
- build_library.py
- SKILL.md
- usage-guide.md
- api_reference.md
- common_queries.md
- search_syntax.md
- SKILL.md
- api_reference.md
- workflow_guide.md
- run_deseq2_analysis.py
- SKILL.md
- align_bowtie2.sh
- SKILL.md
- usage-guide.md
- align_bwa.sh
- SKILL.md
- usage-guide.md
- align_hisat2.sh
- SKILL.md
- usage-guide.md
- align_star.sh
- SKILL.md
- usage-guide.md
- trim_adapters.sh
- SKILL.md
- usage-guide.md
- screen_samples.sh
- SKILL.md
- usage-guide.md
- fastp_pipeline.sh
- SKILL.md
- usage-guide.md
- quality_filter.sh
- SKILL.md
- usage-guide.md
- run_qc_pipeline.sh
- SKILL.md
- usage-guide.md
- check_rrna.sh
- rnaseq_qc.sh
- SKILL.md
- usage-guide.md
- umi_workflow.sh
- SKILL.md
- usage-guide.md
- resolvi_template.py
- run_resolvi.py
- SKILL.md
- cloning_strategy.py
- golden_gate_check.py
- select_enzymes.py
- SKILL.md
- usage-guide.md
- gel_simulation.py
- predict_fragments.py
- SKILL.md
- usage-guide.md
- create_map.py
- plasmid_map.py
- SKILL.md
- usage-guide.md
- circular_plasmid.py
- find_sites.py
- SKILL.md
- usage-guide.md
- detect_orfs.sh
- SKILL.md
- usage-guide.md
- preprocess_riboseq.sh
- SKILL.md
- usage-guide.md
- periodicity_analysis.py
- SKILL.md
- usage-guide.md
- detect_stalling.py
- SKILL.md
- usage-guide.md
- calculate_te.py
- SKILL.md
- usage-guide.md
- kallisto_quant.sh
- salmon_quant.sh
- SKILL.md
- usage-guide.md
- qc_analysis.py
- qc_report.R
- SKILL.md
- usage-guide.md
- count_genes.sh
- process_counts.py
- SKILL.md
- usage-guide.md
- create_tx2gene.R
- tximport_deseq2.R
- SKILL.md
- usage-guide.md
- custom_cm.sh
- parse_infernal.py
- rfam_search.sh
- SKILL.md
- usage-guide.md
- consensus_structure.sh
- rnafold_analysis.py
- SKILL.md
- usage-guide.md
- constrained_folding.py
- shapemapper_analysis.sh
- SKILL.md
- usage-guide.md
- SKILL.md
- analysis_template.py
- api_reference.md
- plotting_guide.md
- standard_workflow.md
- qc_analysis.py
- SKILL.md
- SKILL.md
- SKILL.md
- SKILL.md
- SKILL.md
- SKILL.md
- SKILL.md
- SKILL.md
- SKILL.md
- SKILL.md
- api_reference.md
- SKILL.md
- test_scrna_orchestrator.py
- scrna_orchestrator.py
- SKILL.md
- qc_analysis.py
- qc_core.py
- qc_plotting.py
- README.md
- requirements.txt
- SKILL.md
- scanpy_template.py
- clustering-guide.md
- qc-thresholds.md
- PROTOCOL.md
- scte_template.sh
- usage_notes.md
- SKILL.md
- scvelo_template.py
- differential_kinetics.md
- dynamical_model.md
- velocity_models.md
- rna_velocity_workflow.py
- run_scvelo.py
- SKILL.md
- batch_process.py
- SKILL.md
- usage-guide.md
- compressed_io.py
- SKILL.md
- usage-guide.md
- fastq_quality.py
- SKILL.md
- usage-guide.md
- .gitattributes
- .gitignore
- AGENTS.md
- AUTO_UPDATER_SETUP.md
- build-intel.example.sh
- build-intel.sh
- build-signed.sh
- build-universal.example.sh
- BUILDING_LINUX.md
- BUILDING_WINDOWS.md
- CHANGELOG.md
- CLAUDE.md
- CROSS_PLATFORM_GUIDELINES.md
- index.html
- LICENSE
- package-lock.json
- package.json
- postcss.config.js
- README.md
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/swaruplab/operon
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd operon
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. Node.js
쉬움 추천사전 준비물
npm install
package.json에 명시된 라이브러리들을 내려받아 설치합니다.
npm run tauri dev
이 명령어를 터미널에 그대로 입력해 실행하세요.
npm run tauri build
이 명령어를 터미널에 그대로 입력해 실행하세요.
npm run build:win # Windows: .msi + .exe
배포용으로 코드를 최적화해서 빌드 파일을 생성합니다.
npm run build:linux # Linux: .deb + .rpm + .AppImage
배포용으로 코드를 최적화해서 빌드 파일을 생성합니다.
명령어 실행 후 터미널에 나타나는 주소(보통 http://localhost:3000 형태)를 브라우저에서 열어보세요.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
3. Python
쉬움사전 준비물
⚠️ 이 프로젝트는 규모가 큰 저장소라, 이 방법이 실제 핵심 제품이 아니라 내부 하위 패키지를 가리키는 것일 수 있습니다. README 전체를 함께 확인해보세요.
pip install -r protocols/automated-bioinformatics-pipelines/repo/requirements.txt
requirements.txt 등에 명시된 파이썬 라이브러리를 설치합니다.
jupyter notebook
브라우저에서 노트북(.ipynb) 파일들을 열람하고 실행할 수 있는 Jupyter 화면을 켭니다.
에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.
// repository documentation
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