lamindb
在使用 LaminDB 时应使用此技能，这是一个开源生物学数据框架，使数据可查询、可追溯、可复现且符合 FAIR。适用于管理生物数据集（scRNA-seq、空间、流式细胞术等）、跟踪计算工作流、使用生物本体整理和验证数据、构建数据湖仓，或确保生物研究中的数据谱系和可复现性。涵盖数据管理、注释、本体（基因、细胞类型、疾病、组织）、模式验证、与工作流管理器（Nextflow、Snakemake）和 MLOps 平台（W&B、MLflow）的集成，以及部署策略。
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This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
适用对象：学习与科研。自动收录 · 待核查。
原作者说明节选
从固定版本的 SKILL.md 提取，保留原文语言。以下内容属于作者说明，本站尚未验证安装、兼容或运行结果。
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原文涵盖的主题
- LaminDB
- Overview
- When to Use This Skill
- Core Capabilities
- 1. Core Concepts and Data Lineage
- 2. Data Management and Querying
- 3. Annotation and Validation
- 4. Biological Ontologies
LaminDB is an open-source data framework for biology designed to make data queryable, traceable, reproducible, and FAIR (Findable, Accessible, Interoperable, Reusable). It provides a unified platform that combines lakehouse architecture, lineage tracking, feature stores, biological ontologies, LIMS (Laboratory Information Management System), and ELN (Electronic Lab Notebook) capabilities through a single Python API. Core Value Proposition: Queryability: Search and filter datasets by metadata, features, and ontology terms Traceability: Automatic lineage tracking from raw data through analysis to results Reproducibility: Version control for data, code, and environment FAIR Compliance: Standardized annotations using biological ontologies Use this skill when: Managing biological datasets: scRNA-seq, bulk RNA-seq, spatial transcriptomics, flow cytometry, multi-modal data, EHR data Tracking computational workflows: Notebooks, scripts, pipeline execution (Nextflow, Snakemake, Redun) Curating and validating data: Schema validation, standardization, ontology-based annotation Working with biological ontologies: Genes, proteins, cell types, tissues, diseases, pathways (via Bionty) Building da
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- 来源仓库
- davila7/claude-code-templates
- 源文件
- cli-tool/components/skills/scientific/lamindb/SKILL.md
- 固定版本
- 21be197f100a12b8d0dd9a211cc244c8179f84d3
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本条为自动发现的元数据，尚未完成人工文档核查；适用性与运行结果待核查。
原作者：davila7/claude-code-templates · 原作者仓库元数据。文档核查：未核查。最近来源检查：2026-11-09T15:01:40.128Z。
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