tooluniverse-regulatory-genomics

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English

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Chinese

Regulatory Genomics Research Skill

调控基因组学研究技能

Systematic investigation of gene regulation through transcription factor binding, chromatin state, and regulatory element annotation. Integrates JASPAR (TF motifs), ENCODE (functional genomics experiments), RegulomeDB (regulatory variant scoring), and UCSC cCREs.

通过转录因子结合、染色质状态和调控元件注释对基因调控进行系统性研究。整合了JASPAR（TF基序）、ENCODE（功能基因组学实验）、RegulomeDB（调控变异评分）和UCSC cCREs工具。

Domain Reasoning

领域推理

Regulatory element identification requires converging lines of evidence: sequence conservation alone is insufficient (many conserved sequences are not regulatory), chromatin accessibility is necessary but not sufficient (open chromatin can be structural), TF binding peaks require motif validation, and eQTL evidence ties the element to a transcriptional outcome. No single data type is sufficient. A high-confidence regulatory element requires at least two independent evidence types, and ideally all four.

调控元件的鉴定需要多方面证据的支撑：仅靠序列保守性是不够的（许多保守序列不具备调控功能），染色质可及性是必要条件但非充分条件（开放染色质可能仅具有结构作用），TF结合峰需要基序验证，而eQTL证据可将元件与转录结果关联起来。单一数据类型不足以完成鉴定，高可信度的调控元件需要至少两种独立证据类型，理想情况下四种都具备。

LOOK UP DON'T GUESS

TF binding motifs: retrieve from
```
jaspar_search_matrices
```
and
```
jaspar_get_matrix
```
; do not describe motifs from memory.
Experimental ChIP-seq data: search
```
ENCODE_search_experiments
```
; do not assume a TF has been profiled in a given cell type.
cCRE annotations for a genomic region: call
```
UCSC_get_encode_cCREs
```
with exact coordinates; do not guess element types.
Regulatory impact of a variant: query
```
RegulomeDB_query_variant
```
; never estimate regulatory importance from position alone.

KEY PRINCIPLES:

English-first queries - Use English gene/TF names in all tool calls; respond in user's language
Evidence layering - Combine motif (JASPAR) + experimental (ENCODE ChIP-seq) + variant (RegulomeDB) evidence
Coordinate precision - Genome coordinates must specify assembly (GRCh38 preferred)
Negative results documented - Report when a TF has no ChIP-seq data in ENCODE

TF结合基序：从
```
jaspar_search_matrices
```
和
```
jaspar_get_matrix
```
获取；切勿凭记忆描述基序。
实验ChIP-seq数据：通过
```
ENCODE_search_experiments
```
搜索；切勿假设某一TF在特定细胞类型中已被分析过。
基因组区域的cCRE注释：使用精确坐标调用
```
UCSC_get_encode_cCREs
```
；切勿猜测元件类型。
变异的调控影响：查询
```
RegulomeDB_query_variant
```
；切勿仅根据位置估算调控重要性。

核心原则:

优先使用英文查询 - 在所有工具调用中使用英文基因/TF名称；以用户使用的语言回复
证据分层 - 结合基序（JASPAR）+实验（ENCODE ChIP-seq）+变异（RegulomeDB）证据
坐标精确性 - 基因组坐标必须指定组装版本（优先使用GRCh38）
记录阴性结果 - 当某一TF在ENCODE中无ChIP-seq数据时需进行报告

COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

当分析需要计算（统计、数据处理、评分、富集分析）时，通过Bash编写并运行Python代码。不要描述你会做什么——直接执行并报告实际结果。使用ToolUniverse工具获取数据，然后用Python（pandas、scipy、statsmodels、matplotlib）进行分析。

When to Use

使用场景

"What transcription factors bind near gene X?"
"Does this SNP affect a regulatory element?"
"Find CTCF binding sites in liver tissue"
"What are the enhancers active in this cell type?"
"Show me ChIP-seq experiments for H3K27ac in T cells"
"Is rs1234567 in a regulatory region?"
"What TF motifs overlap this genomic region?"
"Find ENCODE experiments for ATAC-seq in cancer cell lines"

"哪些转录因子结合在基因X附近？"
"这个SNP是否影响调控元件？"
"寻找肝脏组织中的CTCF结合位点"
"该细胞类型中活跃的增强子有哪些？"
"展示T细胞中H3K27ac的ChIP-seq实验"
"rs1234567是否位于调控区域？"
"哪些TF基序与该基因组区域重叠？"
"寻找癌细胞系中ATAC-seq的ENCODE实验"

Key Tools

核心工具

Tool	Purpose	Key Params
`jaspar_search_matrices`	Find TF binding motifs by TF name or organism	`name` , `species` , `collection` , `tax_id`
`jaspar_get_matrix`	Get full PWM/PFM for a specific JASPAR matrix	`matrix_id` (e.g., "MA0139.1")
`JASPAR_get_transcription_factors`	List all TF matrices (paginated)	`page` , `page_size`
`ENCODE_search_experiments`	Search ENCODE ChIP-seq/ATAC-seq/WGBS experiments	`assay_title` , `target` , `biosample_term_name` , `limit`
`ENCODE_search_histone_experiments`	Search histone mark ChIP-seq specifically	`histone_mark` , `biosample_term_name` , `limit`
`ENCODE_search_chromatin_accessibility`	Search ATAC-seq/DNase-seq experiments	`biosample_term_name` , `limit`
`ENCODE_get_experiment`	Get full metadata for a specific ENCODE experiment	`accession` (e.g., "ENCSR000EGM")
`ENCODE_search_annotations`	Search ENCODE cCRE and chromatin state annotations	`annotation_type` , `biosample_term_name` , `limit`
`ENCODE_get_chromatin_state`	Search ChromHMM segmentation data	`biosample_term_name` , `limit`
`UCSC_get_encode_cCREs`	Get cCREs overlapping a genomic region	`chrom` , `start` , `end`
`RegulomeDB_query_variant`	Score regulatory impact of a variant	`rsid` (e.g., "rs4994")
`ENCODE_search_biosamples`	Find available cell lines/tissues in ENCODE	`term_name` , `biosample_type` , `limit`

工具	用途	关键参数
`jaspar_search_matrices`	根据TF名称或物种查找TF结合基序	`name` , `species` , `collection` , `tax_id`
`jaspar_get_matrix`	获取特定JASPAR矩阵的完整PWM/PFM	`matrix_id` （例如："MA0139.1"）
`JASPAR_get_transcription_factors`	列出所有TF矩阵（分页）	`page` , `page_size`
`ENCODE_search_experiments`	搜索ENCODE的ChIP-seq/ATAC-seq/WGBS实验	`assay_title` , `target` , `biosample_term_name` , `limit`
`ENCODE_search_histone_experiments`	专门搜索组蛋白标记的ChIP-seq实验	`histone_mark` , `biosample_term_name` , `limit`
`ENCODE_search_chromatin_accessibility`	搜索ATAC-seq/DNase-seq实验	`biosample_term_name` , `limit`
`ENCODE_get_experiment`	获取特定ENCODE实验的完整元数据	`accession` （例如："ENCSR000EGM"）
`ENCODE_search_annotations`	搜索ENCODE的cCRE和染色质状态注释	`annotation_type` , `biosample_term_name` , `limit`
`ENCODE_get_chromatin_state`	搜索ChromHMM分段数据	`biosample_term_name` , `limit`
`UCSC_get_encode_cCREs`	获取与基因组区域重叠的cCREs	`chrom` , `start` , `end`
`RegulomeDB_query_variant`	对变异的调控影响进行评分	`rsid` （例如："rs4994"）
`ENCODE_search_biosamples`	在ENCODE中查找可用的细胞系/组织	`term_name` , `biosample_type` , `limit`

Workflow

工作流程

Phase 1: TF Motif Discovery (JASPAR)

阶段1：TF基序发现（JASPAR）

When asked about TF binding motifs or what TFs might regulate a gene:

1. jaspar_search_matrices(name="TF_NAME", species="Homo sapiens")
   -> Returns list of matrices with matrix_id, collection, version

2. jaspar_get_matrix(matrix_id="MA0139.1")
   -> Returns full PFM/PWM matrix, sequence logo URL, binding sites URL

3. For broad TF family search:
   jaspar_search_matrices(species="Homo sapiens", collection="CORE")
   -> Filter by TF family name in results

JASPAR Collections:

```
CORE
```
: High-quality, non-redundant matrices (best for most use cases)
```
CNE
```
: Conserved non-coding elements
```
POLII
```
: RNA Pol II binding sites

Key Response Fields:

```
matrix_id
```
: Versioned ID (e.g., "MA0139.1") — use for jaspar_get_matrix
```
name
```
: TF gene symbol
```
sequence_logo
```
: URL to binding site logo PNG/SVG
```
collection
```
: Which JASPAR collection

当被问及TF结合基序或哪些TF可能调控某一基因时：

1. jaspar_search_matrices(name="TF_NAME", species="Homo sapiens")
   -> 返回包含matrix_id、collection、version的矩阵列表

2. jaspar_get_matrix(matrix_id="MA0139.1")
   -> 返回完整的PFM/PWM矩阵、序列logo URL、结合位点URL

3. 如需进行广泛的TF家族搜索：
   jaspar_search_matrices(species="Homo sapiens", collection="CORE")
   -> 在结果中按TF家族名称筛选

JASPAR集合:

```
CORE
```
: 高质量、非冗余矩阵（适用于大多数场景）
```
CNE
```
: 保守非编码元件
```
POLII
```
: RNA Pol II结合位点

关键响应字段:

```
matrix_id
```
: 带版本的ID（例如："MA0139.1"）——用于调用jaspar_get_matrix
```
name
```
: TF基因符号
```
sequence_logo
```
: 结合位点logo的PNG/SVG URL
```
collection
```
: 所属的JASPAR集合

Phase 2: ENCODE Experiment Search

阶段2：ENCODE实验搜索

When looking for ChIP-seq, ATAC-seq, or other functional genomics data:

For TF ChIP-seq:

ENCODE_search_experiments(
    assay_title="TF ChIP-seq",
    target="CTCF",              # TF gene name
    biosample_term_name="HepG2", # Cell line or tissue
    limit=10
)

For histone marks:

ENCODE_search_histone_experiments(
    histone_mark="H3K27ac",         # or H3K4me3, H3K27me3, H3K36me3
    biosample_term_name="liver",
    limit=10
)

For chromatin accessibility:

ENCODE_search_chromatin_accessibility(
    biosample_term_name="T cell",
    limit=10
)

For regulatory annotations (cCREs, ChromHMM):

ENCODE_search_annotations(
    annotation_type="candidate Cis-Regulatory Elements",
    biosample_term_name="K562",
    limit=10
)

Common assay_title values:

```
"TF ChIP-seq"
```
- Transcription factor binding
```
"Histone ChIP-seq"
```
- Histone modification
```
"ATAC-seq"
```
- Chromatin accessibility
```
"DNase-seq"
```
- Open chromatin (older method)
```
"WGBS"
```
- DNA methylation

Note:

ENCODE_search_experiments

returns experiment metadata only (accession, biosample, status). Use

ENCODE_get_experiment(accession)

to get file download links and detailed metadata.

当查找ChIP-seq、ATAC-seq或其他功能基因组学数据时：

TF ChIP-seq实验:

ENCODE_search_experiments(
    assay_title="TF ChIP-seq",
    target="CTCF",              # TF基因名称
    biosample_term_name="HepG2", # 细胞系或组织
    limit=10
)

组蛋白标记实验:

ENCODE_search_histone_experiments(
    histone_mark="H3K27ac",         # 或H3K4me3、H3K27me3、H3K36me3
    biosample_term_name="liver",
    limit=10
)

染色质可及性实验:

ENCODE_search_chromatin_accessibility(
    biosample_term_name="T cell",
    limit=10
)

调控注释实验（cCREs、ChromHMM）:

ENCODE_search_annotations(
    annotation_type="candidate Cis-Regulatory Elements",
    biosample_term_name="K562",
    limit=10
)

常见assay_title值:

```
"TF ChIP-seq"
```
- 转录因子结合
```
"Histone ChIP-seq"
```
- 组蛋白修饰
```
"ATAC-seq"
```
- 染色质可及性
```
"DNase-seq"
```
- 开放染色质（旧方法）
```
"WGBS"
```
- DNA甲基化

注意:

ENCODE_search_experiments

仅返回实验元数据（accession、生物样本、状态）。使用

ENCODE_get_experiment(accession)

获取文件下载链接和详细元数据。

Phase 3: cCRE Annotation (UCSC + ENCODE)

阶段3：cCRE注释（UCSC + ENCODE）

When annotating a specific genomic region:

UCSC_get_encode_cCREs(
    chrom="chr8",       # Chromosome (GRCh38)
    start=37966000,     # Start coordinate
    end=37967000        # End coordinate
)

当注释特定基因组区域时：

UCSC_get_encode_cCREs(
    chrom="chr8",       # 染色体（GRCh38）
    start=37966000,     # 起始坐标
    end=37967000        # 终止坐标
)

Returns cCREs with type: pELS (proximal enhancer), dELS (distal enhancer),

返回包含以下类型的cCREs：pELS（近端增强子）、dELS（远端增强子）、

PLS (promoter-like), CTCF-only, DNase-H3K4me3

PLS（启动子样元件）、仅CTCF结合元件、DNase-H3K4me3元件


**cCRE Types**:
- **PLS** (Promoter-like): High DNase + H3K4me3 + H3K27ac signal near TSS
- **pELS** (Proximal Enhancer): High DNase + H3K27ac, within 2kb of TSS
- **dELS** (Distal Enhancer): High DNase + H3K27ac, >2kb from TSS
- **CTCF-only**: CTCF binding without enhancer marks
- **DNase-H3K4me3**: Unclassified accessible region


**cCRE类型**:
- **PLS**（启动子样元件）：TSS附近具有高DNase + H3K4me3 + H3K27ac信号
- **pELS**（近端增强子）：高DNase + H3K27ac信号，位于TSS 2kb范围内
- **dELS**（远端增强子）：高DNase + H3K27ac信号，距离TSS超过2kb
- **仅CTCF结合元件**：仅存在CTCF结合，无增强子标记
- **DNase-H3K4me3**：未分类的可及区域

Phase 4: Regulatory Variant Scoring (RegulomeDB)

阶段4：调控变异评分（RegulomeDB）

When assessing regulatory impact of a variant:

RegulomeDB_query_variant(rsid="rs4994")

当评估变异的调控影响时：

RegulomeDB_query_variant(rsid="rs4994")

Returns:

regulome_score.ranking: "1a"-"7" (1a = highest regulatory evidence)

regulome_score.ranking: "1a"-"7"（1a表示调控证据最强）

regulome_score.probability: 0-1 continuous score

regulome_score.probability: 0-1范围内的连续评分

tissue_specific_scores: dict of tissue -> score

tissue_specific_scores: 组织->评分的字典

overlapping features: eQTLs, TF binding, DNase peaks, motifs

overlapping features: eQTLs、TF结合、DNase峰、基序


**RegulomeDB Score Interpretation**:
| Rank | Meaning |
|------|---------|
| 1a | eQTL + TF binding + matched TF motif + DNase peak |
| 1b | eQTL + TF binding + DNase peak |
| 1c | eQTL + TF binding or DNase peak |
| 1d | eQTL + motif or protein binding |
| 1e | eQTL + motif hit |
| 1f | eQTL only |
| 2a | TF binding + motif match + DNase |
| 2b | TF binding + matched motif |
| 2c | TF binding with/without motif |
| 3a | DNase peak + motif |
| 3b | DNase peak only |
| 4 | Motif hit only |
| 5 | Proximity to Footprint |
| 6 | Proximity to Footprint + TF |
| 7 | No evidence |

Variants with rank 1a-2b are most likely to affect gene regulation.

---


**RegulomeDB评分解读**:
| 等级 | 含义 |
|------|---------|
| 1a | eQTL + TF结合 + 匹配的TF基序 + DNase峰 |
| 1b | eQTL + TF结合 + DNase峰 |
| 1c | eQTL + TF结合或DNase峰 |
| 1d | eQTL + 基序或蛋白结合 |
| 1e | eQTL + 基序匹配 |
| 1f | 仅eQTL |
| 2a | TF结合 + 基序匹配 + DNase |
| 2b | TF结合 + 匹配的基序 |
| 2c | 带/不带基序的TF结合 |
| 3a | DNase峰 + 基序 |
| 3b | 仅DNase峰 |
| 4 | 仅基序匹配 |
| 5 | 靠近Footprint |
| 6 | 靠近Footprint + TF |
| 7 | 无证据 |

等级为1a-2b的变异最有可能影响基因调控。

---

Tool Parameter Reference

工具参数参考

Tool	Required Params	Optional Params	Notes
`jaspar_search_matrices`	(none — returns all if empty)	`name` , `species` , `collection` , `tax_id` , `page` , `page_size`	Use `name` for TF name search
`jaspar_get_matrix`	`matrix_id`	—	Full version required: "MA0139.1" not "MA0139"
`JASPAR_get_transcription_factors`	(none)	`page` , `page_size`	Paginated; default page_size=10
`jaspar_get_matrix_versions`	`base_id`	—	base_id is unversioned (e.g., "MA0139")
`ENCODE_search_experiments`	(none — returns all if empty)	`assay_title` , `target` , `biosample_term_name` , `limit`	assay_title must match ENCODE vocabulary exactly
`ENCODE_search_histone_experiments`	(none)	`histone_mark` , `biosample_term_name` , `limit`	histone_mark: "H3K27ac", "H3K4me3", etc.
`ENCODE_search_chromatin_accessibility`	(none)	`biosample_term_name` , `limit`	Returns ATAC-seq and DNase-seq
`ENCODE_get_experiment`	`accession`	—	accession: "ENCSR..." format
`ENCODE_search_annotations`	(none)	`annotation_type` , `biosample_term_name` , `limit`	annotation_type: "candidate Cis-Regulatory Elements"
`ENCODE_get_chromatin_state`	(none)	`biosample_term_name` , `limit`	Returns ChromHMM segmentation
`ENCODE_search_biosamples`	(none)	`term_name` , `biosample_type` , `limit`	biosample_type: "cell line", "tissue", "primary cell"
`UCSC_get_encode_cCREs`	`chrom` , `start` , `end`	—	Coordinates in GRCh38; chrom format: "chr1"
`RegulomeDB_query_variant`	`rsid`	—	rsid format: "rs4994" (with rs prefix)

工具	必填参数	可选参数	说明
`jaspar_search_matrices`	无（为空时返回所有结果）	`name` , `species` , `collection` , `tax_id` , `page` , `page_size`	使用 `name` 进行TF名称搜索
`jaspar_get_matrix`	`matrix_id`	—	必须使用完整版本号："MA0139.1"而非"MA0139"
`JASPAR_get_transcription_factors`	无	`page` , `page_size`	分页返回；默认page_size=10
`jaspar_get_matrix_versions`	`base_id`	—	base_id为无版本号的ID（例如："MA0139"）
`ENCODE_search_experiments`	无（为空时返回所有结果）	`assay_title` , `target` , `biosample_term_name` , `limit`	assay_title必须严格匹配ENCODE的标准词汇
`ENCODE_search_histone_experiments`	无	`histone_mark` , `biosample_term_name` , `limit`	histone_mark取值："H3K27ac"、"H3K4me3"等
`ENCODE_search_chromatin_accessibility`	无	`biosample_term_name` , `limit`	返回ATAC-seq和DNase-seq实验
`ENCODE_get_experiment`	`accession`	—	accession格式："ENCSR..."
`ENCODE_search_annotations`	无	`annotation_type` , `biosample_term_name` , `limit`	annotation_type取值："candidate Cis-Regulatory Elements"
`ENCODE_get_chromatin_state`	无	`biosample_term_name` , `limit`	返回ChromHMM分段数据
`ENCODE_search_biosamples`	无	`term_name` , `biosample_type` , `limit`	biosample_type取值："cell line"、"tissue"、"primary cell"
`UCSC_get_encode_cCREs`	`chrom` , `start` , `end`	—	坐标基于GRCh38；chrom格式："chr1"
`RegulomeDB_query_variant`	`rsid`	—	rsid格式："rs4994"（需包含rs前缀）

Common Patterns

常见模式

Pattern 1: TF Binding Site Investigation

模式1：TF结合位点研究

Goal: Find where TF X binds and what motif it recognizes
Flow:
  1. jaspar_search_matrices(name="CTCF") -> get matrix_id
  2. jaspar_get_matrix(matrix_id) -> get full PWM, logo URL
  3. ENCODE_search_experiments(assay_title="TF ChIP-seq", target="CTCF") -> experimental binding data
  4. For specific tissue: add biosample_term_name="HepG2"
Output: Motif logo + experimental binding evidence

目标：查找TF X的结合位置及其识别的基序
流程:
  1. jaspar_search_matrices(name="CTCF") -> 获取matrix_id
  2. jaspar_get_matrix(matrix_id) -> 获取完整PWM、logo URL
  3. ENCODE_search_experiments(assay_title="TF ChIP-seq", target="CTCF") -> 实验结合数据
  4. 针对特定组织：添加biosample_term_name="HepG2"
输出：基序logo + 实验结合证据

Pattern 2: Regulatory Variant Interpretation

模式2：调控变异解读

Goal: Assess if variant rs1234567 affects gene regulation
Flow:
  1. RegulomeDB_query_variant(rsid="rs1234567") -> score + overlapping features
  2. If score <= 2b: ENCODE_search_experiments(target=overlapping_TF) -> experimental evidence
  3. UCSC_get_encode_cCREs(chrom, start, end) -> check if variant in known cCRE
Output: Regulatory score + supporting evidence + cCRE context

目标：评估变异rs1234567是否影响基因调控
流程:
  1. RegulomeDB_query_variant(rsid="rs1234567") -> 评分 + 重叠特征
  2. 如果评分 <= 2b：ENCODE_search_experiments(target=overlapping_TF) -> 实验证据
  3. UCSC_get_encode_cCREs(chrom, start, end) -> 检查变异是否位于已知cCRE中
输出：调控评分 + 支撑证据 + cCRE背景信息

Pattern 3: Cell-Type Regulatory Landscape

模式3：细胞类型调控图谱

Goal: Characterize active enhancers in a cell type
Flow:
  1. ENCODE_search_histone_experiments(histone_mark="H3K27ac", biosample_term_name="K562") -> active enhancers
  2. ENCODE_search_chromatin_accessibility(biosample_term_name="K562") -> open chromatin
  3. ENCODE_search_annotations(annotation_type="candidate Cis-Regulatory Elements", biosample_term_name="K562")
  4. ENCODE_get_chromatin_state(biosample_term_name="K562") -> ChromHMM states
Output: Active regulatory elements specific to the cell type

目标：表征某一细胞类型中活跃的增强子
流程:
  1. ENCODE_search_histone_experiments(histone_mark="H3K27ac", biosample_term_name="K562") -> 活跃增强子
  2. ENCODE_search_chromatin_accessibility(biosample_term_name="K562") -> 开放染色质
  3. ENCODE_search_annotations(annotation_type="candidate Cis-Regulatory Elements", biosample_term_name="K562")
  4. ENCODE_get_chromatin_state(biosample_term_name="K562") -> ChromHMM状态
输出：该细胞类型特有的活跃调控元件

Pattern 4: Gene Regulatory Region Mapping

模式4：基因调控区域定位

Goal: Find all regulatory elements near a gene
Flow:
  1. Get gene coordinates from MyGene_query_genes or ensembl_lookup_gene
  2. UCSC_get_encode_cCREs(chrom, start-50000, end+50000) -> nearby cCREs
  3. ENCODE_search_experiments(target=TF_OF_INTEREST) -> TF binding data
  4. jaspar_search_matrices(name=TF_NAME) -> motif for TF
Output: Map of regulatory elements around gene with evidence types

目标：查找某一基因附近的所有调控元件
流程:
  1. 通过MyGene_query_genes或ensembl_lookup_gene获取基因坐标
  2. UCSC_get_encode_cCREs(chrom, start-50000, end+50000) -> 附近的cCREs
  3. ENCODE_search_experiments(target=TF_OF_INTEREST) -> TF结合数据
  4. jaspar_search_matrices(name=TF_NAME) -> TF的基序
输出：基因周围的调控元件图谱及证据类型

Fallback Strategies

fallback策略

Primary Tool	Fallback	When
`ENCODE_search_experiments` with specific biosample	Remove `biosample_term_name` filter	No results for specific tissue
`jaspar_search_matrices(name=TF)`	`jaspar_search_matrices(name=TF_family)`	TF not found by exact name
`UCSC_get_encode_cCREs`	`ENCODE_search_annotations` without coordinates	If coordinates unknown
`RegulomeDB_query_variant(rsid)`	Use `ENCODE_search_experiments` + `JASPAR` to manually assess overlap	rsid not in RegulomeDB

主工具	替代方案	适用场景
指定生物样本的 `ENCODE_search_experiments`	移除 `biosample_term_name` 筛选条件	特定组织无结果时
`jaspar_search_matrices(name=TF)`	`jaspar_search_matrices(name=TF_family)`	无法通过精确名称找到TF时
`UCSC_get_encode_cCREs`	不指定坐标的 `ENCODE_search_annotations`	坐标未知时
`RegulomeDB_query_variant(rsid)`	使用 `ENCODE_search_experiments` + `JASPAR` 手动评估重叠情况	rsid不在RegulomeDB中时

Limitations

局限性

ENCODE TF ChIP-seq:
```
assay_title="TF ChIP-seq"
```
uses ENCODE's exact controlled vocabulary — avoid "ChIP-seq" (too general)
UCSC cCREs: Coordinates must be in GRCh38 (hg38); liftOver required for hg19 variants
RegulomeDB: Only scores variants with known rsIDs; novel variants not supported
JASPAR: Provides motif databases only — not genomic binding locations; combine with ENCODE for experimental evidence
ENCODE experiment results: The
```
@graph
```
field may be empty if query filters are too restrictive; relax filters and retry

ENCODE TF ChIP-seq：
```
assay_title="TF ChIP-seq"
```
需使用ENCODE的精确受控词汇——避免使用"ChIP-seq"（过于宽泛）
UCSC cCREs：坐标必须基于GRCh38（hg38）；hg19变异需使用liftOver转换
RegulomeDB：仅对已知rsID的变异进行评分；不支持新型变异
JASPAR：仅提供基序数据库——不包含基因组结合位置；需结合ENCODE获取实验证据
ENCODE实验结果：如果查询筛选条件过于严格，
```
@graph
```
字段可能为空；需放宽筛选条件并重试

tooluniverse-regulatory-genomics

Original

Translation

Regulatory Genomics Research Skill

调控基因组学研究技能

Domain Reasoning

领域推理

LOOK UP DON'T GUESS

LOOK UP DON'T GUESS

COMPUTE, DON'T DESCRIBE

COMPUTE, DON'T DESCRIBE

When to Use

使用场景

Key Tools

核心工具

Workflow

工作流程

Phase 1: TF Motif Discovery (JASPAR)

阶段1：TF基序发现（JASPAR）

Phase 2: ENCODE Experiment Search

阶段2：ENCODE实验搜索

Phase 3: cCRE Annotation (UCSC + ENCODE)

阶段3：cCRE注释（UCSC + ENCODE）

Returns cCREs with type: pELS (proximal enhancer), dELS (distal enhancer),

返回包含以下类型的cCREs：pELS（近端增强子）、dELS（远端增强子）、

PLS (promoter-like), CTCF-only, DNase-H3K4me3

PLS（启动子样元件）、仅CTCF结合元件、DNase-H3K4me3元件

Phase 4: Regulatory Variant Scoring (RegulomeDB)

阶段4：调控变异评分（RegulomeDB）

Returns:

返回:

regulome_score.ranking: "1a"-"7" (1a = highest regulatory evidence)

regulome_score.ranking: "1a"-"7"（1a表示调控证据最强）

regulome_score.probability: 0-1 continuous score

regulome_score.probability: 0-1范围内的连续评分

tissue_specific_scores: dict of tissue -> score

tissue_specific_scores: 组织->评分的字典

overlapping features: eQTLs, TF binding, DNase peaks, motifs

overlapping features: eQTLs、TF结合、DNase峰、基序

Tool Parameter Reference

工具参数参考

Common Patterns

常见模式

Pattern 1: TF Binding Site Investigation

模式1：TF结合位点研究

Pattern 2: Regulatory Variant Interpretation

模式2：调控变异解读

Pattern 3: Cell-Type Regulatory Landscape

模式3：细胞类型调控图谱

Pattern 4: Gene Regulatory Region Mapping

模式4：基因调控区域定位

Fallback Strategies

fallback策略

Limitations

局限性