数据与复现生物信息与基因组学FreedomIntelligence/OpenClaw-Medical-Skills数据与复现
BI

bio-research-tools-biomarker-signature-studio

维护者 FreedomIntelligence · 最近更新 2026年4月1日

Build, validate, and visualize multi-omic biomarker signatures.

OpenClawNanoClaw分析处理复现实验bio-research-tools-biomarker-signature-studio🧠 bioos extended suitebioos extended bioinformatics suitebuild

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-research-tools-biomarker-signature-studio

维护者
FreedomIntelligence
许可
MIT
最近更新
2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

  • Design validated biomarker panels that are explainable,stable,、 ready ,用于 translational follow-up. This skill stitches together existing biomarker pipeline tooling,adds configurable feature-selection ensembles,small survival-analysis hook,、 artifact export so downstream lab teams can review QC outputs。
  • 1. QC + Harmonization:Align expression matrices (samples x features) ,支持 metadata,check label balance,、 compute summary stats. 2. Feature Selection Ensemble:Supports Boruta,elastic-net stability,mutual-information top-K,、 mRMR ,支持 optional intersection voting. 3. Model Factory:Trains multiple estimators (Logistic L1,RandomForest,XGBoost if present) under nested CV,picks champion by AUC. 4. Explainability + Export:Produces SHAP tables/plots when packages are available,exports feature rankings 、 model weights. 5. Survival Hook:If metadata contains time_to_event 、 event skill computes concordance ,用于 selected features ,通过 Cox model。
  • All logic lives in scripts/biomarker_signature_studio.py。

原始文档

SKILL.md 摘录

Inputs

  • Expression matrix (--expression): CSV/TSV genes x samples or samples x genes (auto-detected by metadata match).
  • Metadata (--metadata): Must contain --label-column. Optional --id-column (default sample_id), time_to_event, event.
  • Optional gene list for filtering (--feature-list).
  • Output directory (--output-dir), created if missing.

Quick CLI Usage

Key flags:

FlagDescription
--selectorsComma list of selection strategies (boruta, lasso, mrmr, mi_topk).
--modelsModels to evaluate (logit, rf, xgb).
--k-featuresTarget number of features for mrmr/mi_topk.
--survivalEnable Cox evaluation when survival columns exist.
--random-stateReproducibility.
--nested-foldsOuter CV folds (default 5).

Workflow

  1. Load + align inputs, infer orientation, impute missing values.
  2. Standardize features (fit on train set only).
  3. Run requested selectors; create intersection + union candidate lists.
  4. For each selector output run nested CV training across requested models.
  5. Export champion metrics (metrics.json), feature table (selected_features.csv), SHAP summary (shap_summary.csv when available), and survival stats (survival.json).

适用场景

  • Use bio-research-tools-biomarker-signature-studio ,用于 genomics 、 bioinformatics workflows。
  • Apply bio-research-tools-biomarker-signature-studio to sequencing,variant,或 omics analysis tasks。

不适用场景

  • Do not rely on this catalog entry alone ,用于 installation 或 maintenance details。

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