快速查询基因组数据库并完成序列检索、富集分析与可复现生信记录
复制安装指令,让 AI 自动完成配置 · 推荐新手
请帮我安装 askskill 上的 "gget" 技能: 1. 下载 https://raw.githubusercontent.com/affaan-m/ECC/main/skills/scientific-pkg-gget/SKILL.md 2. 保存为 ~/.claude/skills/scientific-pkg-gget/SKILL.md 3. 装好后重载技能,告诉我可以用了
请用 gget 查询人类 TP53 基因的基础信息,包括基因描述、染色体位置、转录本和相关数据库链接,并整理成清晰表格。
返回结构化的 TP53 基因信息表,便于后续研究引用。
请使用 gget 对这段 DNA 序列进行 BLAST 风格相似性检索,列出最相关的匹配对象、物种、相似度和显著性指标,并简要总结结果。
输出相似序列匹配结果列表,并附上简短结论说明可能来源。
请用 gget 对这组差异表达基因做富集分析检查,识别显著通路或功能条目,并生成可复现的分析记录摘要。
给出显著富集条目、统计结果与简要分析记录,便于复现实验过程。
Use this skill when a task needs quick bioinformatics lookup across genomic
reference databases with the gget CLI or Python package.
Use a dedicated workflow instead of gget when the task requires regulated
clinical interpretation, high-throughput production pipelines, or fine-grained
control over database versions and local indexes.
Use a clean Python environment.
python -m venv .venv
. .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install --upgrade gget
gget --help
If uv is available:
uv venv
. .venv/bin/activate
uv pip install gget
Before relying on an older environment, upgrade gget and re-check the module
docs. The upstream databases queried by change over time.
ggetCLI shape:
gget <module> [arguments] [options]
Python shape:
import gget
result = gget.search(["BRCA1"], species="human")
print(result)
Common workflow:
Use current upstream docs for exact arguments. These modules are common first choices:
gget search: find Ensembl IDs from search terms.gget info: retrieve metadata for Ensembl, UniProt, or related IDs.gget seq: fetch nucleotide or amino-acid sequences.gget ref: retrieve reference genome download links.gget blast: run a quick BLAST query.gget blat: locate a sequence against supported genome assemblies.gget muscle: run multiple sequence alignment.gget diamond: run local sequence alignment against reference sequences.gget alphafold and gget pdb: inspect protein-structure references.gget enrichr, gget opentargets, gget archs4, gget bgee, gget cbio,
and gget cosmic: explore enrichment, target, expression, cancer, and disease
association data.Do not assume every module supports every Python version or dependency set. Some optional scientific dependencies have narrower version support than the core package.
Find genes:
gget search -s human brca1 dna repair -o brca1-search.json
Fetch gene metadata:
gget info ENSG00000012048 -o brca1-info.json
Fetch a sequence:
gget seq ENSG00000012048 -o brca1-seq.fa
Run a small BLAST query:
gget blast "MEEPQSDPSVEPPLSQETFSDLWKLLPEN" -l 10 -o blast-results.json
Python example:
import gget
genes = gget.search(["BRCA1", "DNA repair"], species="human")
info = gget.info(["ENSG00000012048"])
sequence = gget.seq("ENSG00000012048")
For scientific outputs, include enough metadata to replay the query.
| Date | gget version | Module | Query | Species/assembly | Output | Notes |
| --- | --- | --- | --- | --- | --- | --- |
| 2026-05-11 | `gget --version` | search | `BRCA1 DNA repair` | human | `brca1-search.json` | Docs checked before run |
Also record:
gget setup.gget.…
为 Quarkus 项目执行发布前验证闭环,涵盖构建、测试、扫描与差异审查。
用自然语言检索并下载 NCBI GEO 的基因表达数据与相关条目