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gget

gget 命令行和 Python 工作流,用于快速基因组数据库查询、序列查找、BLAST 式搜索、富集检查以及可重复的生物信息学证据记录。当任务需要通过 gget CLI 或 Python 包对基因组参考数据库进行快速生物信息学查询时使用。

gget 是什么?

gget 是一个开源命令行和 Python 工作流,专为快速生物信息学查询而设计,允许开发者和研究人员通过单一界面快速访问多个基因组参考数据库。它支持 Ensembl ID 搜索、序列检索、BLAST/BLAT 查询、参考基因组下载、富集分析以及蛋白质结构查找等功能,无需构建完整的本地管道。gget 适用于初步探索和证据记录,并能创建可重复的查询日志,在需要深入分析时可迁移至 Biopython、Snakemake 或 Nextflow 等更专业的工具。该工具在 macOS、Linux 和 Windows 上均可运行,并通过 pip 或 uv 安装,但其上游数据库会随时间变化,因此建议在使用前升级并检查模块文档。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/scientific-pkg-gget

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文档

gget 是做什么的?

当任务需要通过 gget CLI 或 Python 包对基因组参考数据库进行快速生物信息学查询时使用此技能。

使用时机

  • 查找 Ensembl ID、基因元数据、转录本详情或序列。
  • 运行快速 BLAST 或 BLAT 查找,无需构建完整的本地管道。
  • 从 Ensembl 获取参考基因组链接和注释。
  • 通过单一接口查询蛋白质结构、通路、癌症、表达或疾病关联模块。
  • 在进行 Biopython、Snakemake、Nextflow、BLAST+ 或特定数据库客户端等更重型的工具之前,创建可重复的初步证据日志。

当任务需要受监管的临床解读、高吞吐量生产管道或对数据库版本和本地索引进行精细控制时,请使用专用工作流代替 gget。

安装

使用干净的 Python 环境。

python -m venv .venv
. .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install --upgrade gget
gget --help

如果 uv 可用:

uv venv
. .venv/bin/activate
uv pip install gget

在依赖旧环境之前,升级 gget 并重新检查模块文档。gget 查询的上游数据库会随时间变化。

基本模式

CLI 格式:

gget <module> [arguments] [options]

Python 格式:

import gget

result = gget.search(["BRCA1"], species="human")
print(result)

常见工作流:

  1. 确定所需物种、组装、基因 ID 类型和数据库。
  2. 检查当前模块文档以获取参数。
  3. 先运行一个小型查询。
  4. 使用明确的文件名和日期保存输出。
  5. 记录模块名称、版本、参数和数据库假设。

常见模块

使用最新的上游文档获取确切参数。这些模块是常见首选:

  • gget search:通过搜索词查找 Ensembl ID。
  • gget info:检索 Ensembl、UniProt 或相关 ID 的元数据。
  • gget seq:获取核苷酸或氨基酸序列。
  • gget ref:检索参考基因组下载链接。
  • gget blast:运行快速 BLAST 查询。
  • gget blat:将序列定位到支持的基因组组装。
  • gget muscle:运行多序列比对。
  • gget diamond:对参考序列进行本地序列比对。
  • gget alphafold 和 gget pdb:检查蛋白质结构参考。
  • gget enrichr、gget opentargets、gget archs4、gget bgee、gget cbio 和 gget cosmic:探索富集、靶点、表达、癌症和疾病关联数据。

不要假设每个模块都支持每个 Python 版本或依赖集。某些可选的科学依赖项具有比核心包更窄的版本支持。

快速示例

查找基因:

gget search -s human brca1 dna repair -o brca1-search.json

获取基因元数据:

gget info ENSG00000012048 -o brca1-info.json

获取序列:

gget seq ENSG00000012048 -o brca1-seq.fa

运行小型 BLAST 查询:

gget blast "MEEPQSDPSVEPPLSQETFSDLWKLLPEN" -l 10 -o blast-results.json

Python 示例:

import gget

genes = gget.search(["BRCA1", "DNA repair"], species="human")
info = gget.info(["ENSG00000012048"])
sequence = gget.seq("ENSG00000012048")

可重复性日志

对于科学输出,包含足够的元数据以重放查询。

| 日期 | gget 版本 | 模块 | 查询 | 物种/组装 | 输出 | 备注 |
| --- | --- | --- | --- | --- | --- | --- |
| 2026-05-11 | `gget --version` | search | `BRCA1 DNA repair` | human | `brca1-search.json` | 运行前检查了文档 |

还要记录:

  • Python 版本和环境管理器。
  • 通过 gget setup 安装的任何可选依赖项。
  • 查询返回的特定于数据库的标识符。
  • 输出是 JSON、CSV、FASTA 还是 DataFrame 导出。
  • 通过升级 gget 解决的所有失败。

审查清单

  • 您是否已升级或验证已安装的 gget 版本?
  • 在使用参数前,您是否检查了最新的上游模块文档?
  • 物种或组装是否明确?
  • 标识符是否完全保留,包括 Ensembl/UniProt 前缀?
  • 结果是否被标记为数据库输出而非临床解读?
  • 查询是否可通过保存的命令或 Python 片段重现?
  • 可选依赖项是否安装在隔离的环境中?

参考资料

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/ECC

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

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