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Search ENCODE Experiments

encode_search_experiments
Read-onlyIdempotent

Search ENCODE functional genomics experiments using filters like assay type, organism, tissue, cell line, or free text to find relevant datasets for analysis.

Instructions

Search ENCODE experiments with comprehensive filters.

Examples:

  • Find all Histone ChIP-seq on human pancreas tissue: assay_title="Histone ChIP-seq", organ="pancreas", biosample_type="tissue"

  • Find ATAC-seq on human brain: assay_title="ATAC-seq", organ="brain"

  • Find RNA-seq on GM12878 cell line: assay_title="RNA-seq", biosample_term_name="GM12878"

  • Find ChIP-seq targeting H3K27me3: assay_title="Histone ChIP-seq", target="H3K27me3"

  • Find all mouse liver experiments: organism="Mus musculus", organ="liver"

  • Free text search: search_term="CRISPR screen pancreatic"

Common assay_title values: "Histone ChIP-seq", "TF ChIP-seq", "ATAC-seq", "DNase-seq", "RNA-seq", "total RNA-seq", "WGBS", "Hi-C", "CUT&RUN", "CUT&Tag", "STARR-seq", "MPRA", "eCLIP", "CRISPR screen"

Common organ values: "pancreas", "liver", "brain", "heart", "kidney", "lung", "intestine", "skin of body", "blood", "spleen", "thymus"

biosample_type values: "tissue", "cell line", "primary cell", "in vitro differentiated cells", "organoid"

WHEN TO USE: Use as the primary entry point when users want to find experiments. Start with encode_get_facets if unsure what filters to use. RELATED TOOLS: encode_get_facets, encode_get_metadata, encode_search_files

Args: assay_title: Assay type (e.g., "Histone ChIP-seq", "ATAC-seq", "RNA-seq") organism: Species (default: "Homo sapiens"). Also: "Mus musculus" organ: Organ/tissue system (e.g., "pancreas", "brain", "liver") biosample_type: Sample classification ("tissue", "cell line", "primary cell", "organoid") biosample_term_name: Specific cell/tissue name (e.g., "GM12878", "HepG2", "pancreas") target: ChIP/CUT&RUN target (e.g., "H3K27me3", "CTCF", "p300") status: Data status (default: "released"). Also: "archived", "revoked" lab: Submitting lab name award: Funding project assembly: Genome assembly (e.g., "GRCh38", "mm10") replication_type: "isogenic", "anisogenic", or "unreplicated" life_stage: "embryonic", "postnatal", "child", "adult" sex: "male", "female", "mixed" treatment: Treatment name if perturbation experiment genetic_modification: Modification type ("CRISPR", "RNAi") perturbed: True for perturbation experiments only search_term: Free text search across all fields date_released_from: Start date (YYYY-MM-DD) for date range filter date_released_to: End date (YYYY-MM-DD) for date range filter limit: Max results to return (default 25, use larger for comprehensive searches) offset: Skip first N results (for pagination)

Returns: JSON with experiment results, total count, and pagination info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assay_titleNo
organismNoHomo sapiens
organNo
biosample_typeNo
biosample_term_nameNo
targetNo
statusNoreleased
labNo
awardNo
assemblyNo
replication_typeNo
life_stageNo
sexNo
treatmentNo
genetic_modificationNo
perturbedNo
search_termNo
date_released_fromNo
date_released_toNo
limitNo
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, open-world, idempotent, and non-destructive behavior. The description adds value by providing examples of common filter values, explaining default parameters (e.g., organism default to 'Homo sapiens'), and noting pagination behavior with limit/offset. It doesn't contradict annotations and offers useful context beyond them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (examples, common values, usage guidelines, args, returns) and is appropriately sized for a complex tool. While comprehensive, every sentence adds value, such as practical examples and parameter details, though it could be slightly more front-loaded by moving key usage guidance earlier.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (21 parameters, 0% schema coverage), the description is highly complete. It covers purpose, usage, parameters with semantics, examples, and return format. With annotations providing safety context and an output schema indicating JSON results, the description fills all necessary gaps, making it fully adequate for agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage and 21 parameters, the description fully compensates by providing detailed parameter explanations, including defaults, examples, and common values for key filters like assay_title, organ, and biosample_type. It adds significant meaning beyond the bare schema, making parameters understandable and actionable.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches ENCODE experiments with comprehensive filters, distinguishing it from siblings like encode_get_facets (for exploring filters) and encode_search_files (for searching files). It specifies the resource (ENCODE experiments) and action (search with filters), making the purpose explicit and differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a dedicated 'WHEN TO USE' section that explicitly states to use it as the primary entry point for finding experiments and to start with encode_get_facets if unsure about filters. It also lists related tools, providing clear guidance on when to use this tool versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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