Workflow for read alignment, sorting, indexing, mapping statistics, and downstream-ready alignment artifacts.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Workflow for orthology, synteny, ancestral reconstruction, and evolutionary comparison across genomes.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Reference examples assume recent stable releases of the preferred tools, especially orthology and the other tools listed below.
Before using code or command patterns, verify installed versions match the environment:
python -c "import <module>; print(<module>.__version__)"<tool> --versionWorkflow for orthology, synteny, ancestral reconstruction, and evolutionary comparison across genomes.
references/technical_reference.md when you need deeper tool-selection rules, environment adaptation notes, or extra validation guidance.SKILL.md as the main execution path and load the reference file only when the task or failure mode needs the extra detail.Preferred starting point: orthology
Inputs: assemblies, gene annotations, optional phylogenetic context
Outputs: ortholog tables, synteny outputs, evolutionary comparison summaries
Clarify whether the task is gene-level, synteny-level, or phylogenomic.
Use consistent naming, feature models, and assemblies before comparing genomes.
Run orthology, synteny, or evolutionary analyses appropriate to the question.
Separate technical annotation differences from genuine biological divergence.
Save tables and figures that highlight conserved versus lineage-specific patterns.
results/ for final tables and serialized objectsfigures/ for plots and static visual exportsqc/ for checks that justify downstream interpretationortholog tablessynteny outputsevolutionary comparison summariesVariant CallingCopy NumberLong-Read GenomicsGenome Assembly아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Workflow for read alignment, sorting, indexing, mapping statistics, and downstream-ready alignment artifacts.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Validate protein designs using AlphaFold2 structure prediction. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer. For faster single-chain prediction, use esm. For QC thresholds, use protein-qc.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AlphaFold2 / AlphaFold-Multimer structure prediction for validation and confidence scoring. Use this skill when: (1) Validating designed sequences fold correctly, (2) Predicting binder-target complex structures, (3) Calculating confidence metrics (pLDDT, pTM, ipTM), (4) Self-consistency validation of designs, (5) Multi-chain complex prediction with AlphaFold-Multimer. For faster single-chain prediction, use esm2-sequence-scoring. For QC thresholds, use protein-design-qc.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Workflow for event-level and isoform-level splicing analysis with sashimi-ready outputs and splice QC.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
ATAC-seq processing with assay QC, MACS3 peak calling, consensus peak matrices, differential accessibility, and motif or footprint follow-up.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate. For backbone-only generation, use rfdiffusion. For QC thresholds, use protein-qc. For tool selection guidance, use binder-design.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.