Results for “genetic-compatibility”

Use to build Science's data, code, and materials availability — mandatory deposition in approved repositories, accession numbers, a compliant data-availability statement, and materials/reagent sharing.

Manage feature manifests for code traceability. Use when creating new features, updating existing features, checking feature health, or exploring the feature-to-code relationship. Activates for manifest validation, feature creation, changelog updates, and traceability queries.

Access ClinPGx pharmacogenomics data (the successor to PharmGKB) to query gene-drug interactions, CPIC/DPWG dosing guidelines, drug labels, and pharmacogene records. Use when interpreting pharmacogenes (CYP2D6, CYP2C19, TPMT, DPYD, SLCO1B1), looking up genotype-guided drug dosing, checking PGx drug-safety associations (e.g. HLA-B*57:01 and abacavir), or supporting precision medicine and clinical pharmacogenomics decisions. For star-allele definitions/frequencies see PharmVar; for germline/somatic variant pathogenicity see alterlab-clinvar. Part of the AlterLab Academic Skills suite.

Triage mutation testing results by combining survived mutants, unnecessary test statements, and code graph analysis to identify false positives, missing test coverage, and fuzzing targets.

Combined verification — recite (description quality via cold-read prediction) + validate (schema compliance) + review (health checks). Use as a quality gate after creating notes or as periodic maintenance. Triggers on "/verify", "/verify [note]", "verify note quality", "check note health".

Query NCBI Gene via the E-utilities and Datasets APIs, searching by gene symbol or Gene ID and retrieving gene information (RefSeqs, GO terms, genomic locations, associated phenotypes) including batch lookups. Use when resolving gene symbols to IDs, annotating gene lists, or pulling functional and positional gene metadata for downstream analysis. Part of the AlterLab Academic Skills suite.

Process and analyze mass spectrometry data: import spectra from MGF, mzML, MSP, and JSON formats; apply 40+ filters for metadata harmonization and peak cleaning; compute spectral similarities (cosine, modified cosine) for compound identification; build reproducible processing pipelines.

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

Reconcile a processkit project’s migrations, health findings, and repository collaboration queue. Use when resolving all migrations, pk-doctor findings, GitHub issues, pull requests, or release blockers.

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

Spectral similarity and compound identification for metabolomics. Use for comparing mass spectra, computing similarity scores (cosine, modified cosine), and identifying unknown compounds from spectral libraries. Best for metabolite identification, spectral matching, library searching. For full LC-MS/MS proteomics pipelines use pyopenms.

Configure Gemini and Codex CLI tools with Cloudflare AI Gateway endpoints and MCP servers.

SSOT（Single Source of Truth）と実際のファイル/設定の整合性をチェックし、乖離があれば修正するスキル。 「SSOTチェックして」「SSOT整合性チェックして」「SSOT整理して」「SSOTのズレを直して」 「00_SYSTEM更新して」「乖離を修正して」と言った時にトリガーする。 /ssot-check でも呼び出せる。

Composite skill — take a PR from "I think it's ready" to merged with full gate verification. Chains pr-merge-readiness (verdict) → ci-watch / gh-fix-ci (if blockers) → gh-address-comments (if review needed) → ship (when verdict is MERGE). Use as the one-call answer to "can I merge this?" instead of running 4 skills sequentially.

A git SHA pins the transformation.

Gemini: A Family of Highly Capable Multimodal Models

CAP Theorem

Universal opt-out mechanism implementation across US state privacy laws. Covers Global Privacy Control (GPC) signal technical implementation, state-by-state recognition requirements, browser detection methods, authenticated vs unauthenticated handling, and compliance testing.

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

Runs high-performance genomic interval analysis with gtars (databio), a Rust toolkit with Python bindings — the performance-critical backend for the geniml ML library. Use when computing overlaps/jaccard/coverage between BED region sets, indexing intervals with IGD, generating uniwig accumulation/coverage tracks, tokenizing genomic regions for ML, splitting single-cell fragments into pseudobulks, or computing GA4GH refget sequence digests. NOT for training region embeddings (use alterlab-geniml) or non-genomic spatial joins (use alterlab-geopandas). Part of the AlterLab Academic Skills suite.