quickgo-database

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English

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Translation

Chinese

QuickGO Database Skill

QuickGO数据库技能

GO (Gene Ontology) annotations are one of the main ways to label a gene's function. QuickGO is a fast, web-based browser for the GO and Evidence & Conclusion Ontology (ECO), maintained by the Gene Ontology Annotation (GOA) group at EMBL-EBI.

It provides a centralised resource to explore the functional attributes of gene products (proteins, RNA, and complexes). It is a primary tool for functional annotation mapping since it allows you to link a gene (e.g., USH2A) to its specific biological processes (e.g. sensory perception of light stimulus), molecular functions, and cellular components.

GO（Gene Ontology）注释是标注基因功能的主要方式之一。QuickGO是由EMBL-EBI的Gene Ontology Annotation（GOA）小组维护的、基于网页的GO和Evidence & Conclusion Ontology（ECO）快速浏览器。

它提供了一个集中式资源，用于探索基因产物（蛋白质、RNA和复合物）的功能属性。作为功能注释映射的核心工具，它可以将基因（例如USH2A）与其特定的生物过程（例如光刺激的感官感知）、分子功能和细胞组分关联起来。

Prerequisites

前置条件

uv
: Read the
```
uv
```
skill and follow its Setup instructions to ensure
```
uv
```
is installed and on PATH.
User Notification: If LICENSE_NOTIFICATION.txt does not already exist in this skill directory then (1) prominently notify the user to check the terms at https://www.ebi.ac.uk/QuickGO/ and https://www.ebi.ac.uk/QuickGO/api/index.html, then (2) create the file recording the notification text and timestamp.

uv
：阅读
```
uv
```
技能并按照其设置说明确保
```
uv
```
已安装且在PATH路径中。
用户通知：如果此技能目录中不存在LICENSE_NOTIFICATION.txt文件，则(1) 显著通知用户查看https://www.ebi.ac.uk/QuickGO/和https://www.ebi.ac.uk/QuickGO/api/index.html上的条款，然后(2) 创建记录通知文本和时间戳的文件。

Usage

使用方法

This skill provides a Python CLI wrapper

scripts/quickgo_tool.py

that queries the QuickGO REST API. It handles formatting the requests, respecting rate limits, and safely storing the potentially large JSON responses.

此技能提供了一个Python CLI包装器

scripts/quickgo_tool.py

，用于查询QuickGO REST API。它处理请求格式化、遵守速率限制，并安全存储可能较大的JSON响应。

Core Rules

核心规则

Use the Wrapper: ALWAYS execute the provided helper scripts to query the database rather than accessing the database directly. The scripts automatically enforce the required rate limit gracefully.
Pagination & Limits: Restrict endpoints to a maximum of 100 results per page using
```
--limit 100
```
and the
```
--page
```
parameter for larger datasets.
Output Files: Always use the
```
--output
```
flag to save responses to a file incrementally or parse via
```
jq
```
.
Evidence Codes: Prioritize experimental evidence (
```
ECO:0000269
```
) over electronic (
```
ECO:0000501
```
) to avoid noisy predictions.
Taxon Filtering: Use
```
--taxonId 9606
```
to restrict results to Human when analysing clinical or human genomic data.
Notification: If this skill is used, ensure this is mentioned in the output.

The tool has four main subcommands:

go
: For retrieving information about GO terms (e.g. definitions, ancestors, descendants, and slims). See references/go_terms.md.
annotation
: For finding functional annotations linking gene products to GO terms. This is your primary functional mapper. See references/annotations.md.
geneproduct
: For resolving gene symbols (like
```
PROC
```
) to their formal database identifiers. See references/gene_products.md.
eco
: For Evidence & Conclusion Ontology terms (used in annotations to indicate how an annotation was derived, e.g. experimental vs electronic). See references/eco_terms.md.

使用包装器：始终执行提供的辅助脚本来查询数据库，而非直接访问数据库。脚本会自动优雅地强制执行所需的速率限制。
分页与限制：使用
```
--limit 100
```
和
```
--page
```
参数限制每个端点的最大结果数为100条，以处理更大的数据集。
输出文件：始终使用
```
--output
```
标志将响应增量保存到文件中，或通过
```
jq
```
解析。
证据代码：优先选择实验证据（
```
ECO:0000269
```
）而非电子证据（
```
ECO:0000501
```
），以避免嘈杂的预测结果。
分类群过滤：分析临床或人类基因组数据时，使用
```
--taxonId 9606
```
将结果限制为人类。
通知：如果使用此技能，请确保在输出中提及这一点。

该工具包含四个主要子命令：

go
：用于检索GO术语的相关信息（例如定义、祖先、后代和精简集）。请参阅references/go_terms.md。
annotation
：用于查找将基因产物与GO术语关联的功能注释。这是您的核心功能映射工具。请参阅references/annotations.md。
geneproduct
：用于将基因符号（如
```
PROC
```
）解析为其正式的数据库标识符。请参阅references/gene_products.md。
eco
：用于处理Evidence & Conclusion Ontology术语（在注释中用于指示注释的来源，例如实验来源 vs 电子来源）。请参阅references/eco_terms.md。

Common Workflows

常见工作流

1. Map a gene to its functions (Annotations)

1. 将基因映射到其功能（注释）

To find out what a gene does, you must first resolve its symbol to a UniProtKB ID, and then query its annotations. Often it is best to filter for experimental evidence (e.g.

ECO:0000269

for EXP, or others like IDA, IMP) to avoid noisy electronic predictions.

bash

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要了解某个基因的功能，必须先将其符号解析为UniProtKB ID，然后查询其注释。通常最好过滤出实验证据（例如

ECO:0000269

对应EXP，或IDA、IMP等其他类型），以避免嘈杂的电子预测结果。

bash

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Step 1: Find the UniProtKB ID for human (9606) gene PROC

步骤1：查找人类（9606）基因PROC的UniProtKB ID

uv run scripts/quickgo_tool.py geneproduct search --query "PROC" --taxonId 9606 --limit 5 --output proc_id.json

(Look at proc_id.json, observe the ID is e.g., UniProtKB:P04070)

（查看proc_id.json，观察ID例如为UniProtKB:P04070）

Step 2: Find experimental GO annotations for that ID

步骤2：查找该ID的实验GO注释

uv run scripts/quickgo_tool.py annotation search --geneProductId "UniProtKB:P04070" --taxonId 9606 --evidenceCode "ECO:0000269" --limit 50 --output proc_annotations.json

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uv run scripts/quickgo_tool.py annotation search --geneProductId "UniProtKB:P04070" --taxonId 9606 --evidenceCode "ECO:0000269" --limit 50 --output proc_annotations.json

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2. Find all genes in a pathway

2. 查找通路中的所有基因

To find all genes annotated to a specific GO term (e.g., GO:0003700 for "transcription factor activity"):

bash

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要查找所有注释到特定GO术语（例如GO:0003700对应“转录因子活性”）的基因：

bash

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Find human genes with this specific molecular function

查找具有此特定分子功能的人类基因

uv run scripts/quickgo_tool.py annotation search --goId "GO:0003700" --taxonId 9606 --limit 50 --output tf_genes.json

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uv run scripts/quickgo_tool.py annotation search --goId "GO:0003700" --taxonId 9606 --limit 50 --output tf_genes.json

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3. Explore the GO Hierarchy

3. 探索GO层级结构

To check if a specific GO term is a descendant of a broader category, or to fetch its definition:

bash

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要检查特定GO术语是否属于更广泛类别的子项，或获取其定义：

bash

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Fetch term details (definitions, synonyms)

获取术语详情（定义、同义词）

uv run scripts/quickgo_tool.py go terms --ids "GO:0003150" --output term_details.json

Check ancestry (e.g., is GO:0001917 a child of something?)

检查祖先关系（例如，GO:0001917是否为某个术语的子项？）

uv run scripts/quickgo_tool.py go terms --ids "GO:0001917" --relation ancestors --output term_ancestors.json

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uv run scripts/quickgo_tool.py go terms --ids "GO:0001917" --relation ancestors --output term_ancestors.json

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4. Create a GO Slim Summary

4. 创建GO精简集摘要

If you have a list of candidate genes and want a high-level functional summary, you can map them up to a predefined GO Slim. First, fetch the annotations for the genes to extract their GO IDs, then pass those IDs to the slim endpoint:

bash

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如果您有候选基因列表并想要获得高级功能摘要，可以将它们映射到预定义的GO精简集。首先，获取这些基因的注释以提取其GO ID，然后将这些ID传递给精简集端点：

bash

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Step 1: Find GO IDs for candidate genes (e.g., via their UniProt IDs, fetching their annotations)

步骤1：查找候选基因的GO ID（例如，通过其UniProt ID获取注释）

... (output yields e.g., GO:0006915,GO:0008219)

...（输出结果例如为GO:0006915,GO:0008219）

Step 2: Create a slim summary from those specific GO IDs

步骤2：从这些特定GO ID创建精简集摘要

uv run scripts/quickgo_tool.py go slim --slimsToIds "GO:0005575,GO:0008150,GO:0003674" --slimsFromIds "GO:0006915,GO:0008219" --output my_slim.json

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uv run scripts/quickgo_tool.py go slim --slimsToIds "GO:0005575,GO:0008150,GO:0003674" --slimsFromIds "GO:0006915,GO:0008219" --output my_slim.json

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