Query ReMap 2022 TF ChIP-seq peak database via REST API and BED downloads. Retrieve TF peaks overlapping a region (chr:start-end), peaks near a gene, TFs by species, peaks filtered by biotype (promoter, enhancer), and BED files for a TF-cell type pair.
SkillScore95Maintained
Automatic
◆Research pack
Last verified 8/24/2026
What it changes
Passed 21 of 22 test cases with the skill, and 8 of 22 without it.
Without skill36%
With skill95%
Checks it passed that the model alone missed
The GET request passes assembly set to hg38.
The API query parameter sets assembly to mm10.
The GET request query parameters set name to CTCF.
and 20 more in the full report
14 fixed7 passed either way0 still failing1 broke
Pass-rate lift
+59 pp
Tokens
+269%
Agent turns
0%
Response time
-37%
Model gemini-3.6-flashMeasured 8/24/2026v121 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 14
Prompt
Write a Python snippet to retrieve overall database metrics (such as peak and TF counts) for the hg38 assembly from the ReMap REST service.
What was checked, without and with the skill
Checked
Without skill
With skill
The script requests https://remap2022.univ-amu.fr/api/v1/stats/
Missed
Passed
case-12 · gemini-3.6-flash · 8/24/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md695 linessingle file
ReMap Database
Overview
ReMap 2022 is an integrative database of transcription factor (TF), cofactor, and chromatin regulator binding sites derived from uniformly reprocessed ChIP-seq experiments. The 2022 release catalogs 165 million non-redundant peaks from 8,113 ChIP-seq datasets covering 1,210 TFs across human (hg38/hg19), mouse (mm10), Drosophila, and Arabidopsis genomes. All peaks are called with a consistent pipeline from public GEO/ArrayExpress experiments. Access is via the ReMap 2022 REST API at https://remap2022.univ-amu.fr/api/ and bulk BED file downloads; no authentication required.
When to Use
Finding all TFs with ChIP-seq peaks overlapping a genomic region of interest (e.g., a GWAS SNP locus or candidate enhancer)
Retrieving TF peaks near a gene's transcription start site to map its proximal regulatory landscape
Listing all TFs available in ReMap for human or mouse with their peak and dataset counts
Filtering ChIP-seq peaks by regulatory biotype annotation (promoter, enhancer, exon, intron, intergenic) for a TF in a specific cell line
Downloading a BED file of all binding peaks for a TF across all cell types for offline analysis
Identifying co-binding TFs at a locus by querying all overlapping peaks and grouping by TF name
Use jaspar-database instead when you need PWM/PFM sequence models of TF binding specificity rather than ChIP-seq peak locations
For ENCODE-specific regulatory tracks and accessibility data use encode-database; ReMap aggregates TF binding peaks from many sources including ENCODE
Prerequisites
Python packages: requests, pandas, matplotlib
Data requirements: genomic coordinates (GRCh38/hg38 or hg19), gene names, or TF names
Environment: internet connection; no API key required
Rate limits: no official published limits; use time.sleep(0.5) between batch requests to avoid server overload
Note: The ReMap API is a research API; endpoint availability may vary. All examples include a BED download fallback.
pip install requests pandas matplotlib
Quick Start
import requests
REMAP_API = "https://remap2022.univ-amu.fr/api/v1"
# Query TF peaks overlapping a genomic region
r = requests.get(f"{REMAP_API}/peaks/overlap/", params={
"chr": "chr17",
"start": 7_670_000,