| name | unibind-database |
| description | >- Queries the UniBind database for experimentally validated transcription factor (TF) binding sites. Use when retrieving direct TF-DNA interaction datasets, downloading binding site coordinates (BED/FASTA) for local analysis, or listing available datasets by species, cell line, or TF name. Don't use to query specific intervals, locations, genes, motif models or expression data. |
UniBind Database Skill
UniBind is a database of direct TF–DNA interactions across 9 species,
integrating ChIP-seq peaks with JASPAR TF binding profiles via the DAMO
framework.
Prerequisites
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://unibind.uio.no/ and https://unibind.uio.no/api/overview, then (2)
create the file recording the notification text and timestamp.
Quick Start
Query commands print JSON to stdout by default. Most outputs are small enough to
read directly. For large outputs (list_cell_lines, list_tfs), pipe through
jq to extract only the fields you need.
uv run <SKILL DIR>/scripts/unibind_api.py list_species
The download_tfbs command writes BED/FASTA files to --output-dir instead.
You may optionally use --output <path> on any query command to save results to
a file if needed.
Core Rules
- 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.
- Output: Query commands print JSON to stdout. Most responses are compact
and can be read directly.
- Large Results:
list_cell_lines and list_tfs produce large output.
Pipe these through jq to extract specific fields rather than reading the
full output into context.
- Saving to File: Use
--output <path> when you need to reference the
data later or when processing very large results with jq.
- Pagination: Use
--page and --page-size (max 1000) to chunk large
result sets.
- Ordering: Use
--order field_name (prefix with - for descending) on
any list command.
- Notification: If this skill is used, ensure this is mentioned in the
output.
Utility Scripts
Replace <SKILL DIR> with the absolute path to this skill's directory.
1. List Species
uv run <SKILL DIR>/scripts/unibind_api.py list_species
2. List Collections
uv run <SKILL DIR>/scripts/unibind_api.py list_collections
3. List Cell Lines & TFs (large output — use jp)
These commands return large datasets. Use uvx --from jmespath jp to extract
only the fields you need.
uv run <SKILL DIR>/scripts/unibind_api.py list_cell_lines | uvx --from jmespath jp "results[].name"
uv run <SKILL DIR>/scripts/unibind_api.py list_tfs | uvx --from jmespath jp "results[].tf_name"
4. List and Filter Datasets (and Profile-Specific Datasets)
Filter datasets using the following arguments:
--species (e.g., "Homo sapiens")--tf-name (e.g., "CTCF")--cell-line (e.g., "mESC")--collection (e.g., Permissive, Robust)--search (a search term)--biological-condition (biological condition or source)--data-source (source of data, e.g., "ENCODE")--has-pvalue ("true" or "false")--identifier (e.g., "GSE60130")--jaspar-id (JASPAR database profile matrix ID)--model (prediction model)--summary (summary filter)--threshold-pvalue (p-value threshold)
Use list_datasets for standard datasets, or list_specific_datasets for
profile-specific queries.
uv run <SKILL DIR>/scripts/unibind_api.py list_datasets --species "Homo sapiens" --tf-name "CTCF" --data-source "ENCODE"
uv run <SKILL DIR>/scripts/unibind_api.py list_specific_datasets --species "Mus musculus" --cell-line "mESC"
5. Get Dataset Details
uv run <SKILL DIR>/scripts/unibind_api.py get_dataset "EXP047889.HMLE-Twist-ER_breast_cancer.SMAD3"
6. Download TFBS Files (BED / FASTA)
Downloads all TFBS files for a dataset to a local directory. Use --format bed
(default) or --format fasta.
uv run <SKILL DIR>/scripts/unibind_api.py download_tfbs "EXP047889.HMLE-Twist-ER_breast_cancer.SMAD3" --output-dir /tmp/tfbs --format bed
Anti-Patterns
- DON'T attempt to use the UniBind API to query specific genomic
intervals, locations, or genes.
- DON'T guess or hallucinate genome coordinates. Always use
ensembl-database as an external check if you're pulling local BED tracks
for offline bedtools intersection.
- DON'T use for motif models (PFMs). Use the jaspar-database skill
instead.
- DON'T use for gene expression data. UniBind only stores binding events.
- DON'T assume tissue-specific expression from dataset lists alone.
- DON'T use
cat to read large JSON output files into context. The output
is too large. Use jq or write your own code to parse the output files.
