Agent skill · Databases

remap-database

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. Use for TF co-occupancy, regulatory annotation, and TF binding atlases. Use jaspar-database for PWM motifs; encode-database for ENCODE tracks.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill remap-database --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 28 KB
Bundled scripts: none
Path: skills/sciagent/remap-database/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

Retrieves transcription factor (TF) ChIP-seq peak data from the ReMap 2022 REST API and BED downloads. It provides concrete queries for: overlapping peaks within a region, peaks near a gene, listing TFs for a genome assembly, peaks for a named TF, and biotype-filtered peaks. It also guides on using JASPAR for PWM motifs and ENCODE tracks via encode-database.

How it works

  • Uses the REST API at https://remap2022.univ-amu.fr/api/v1 to perform various queries:
    • /peaks/overlap/ to fetch peaks overlapping a specified region (chr, start, end, assembly).
    • /peaks/gene/ to fetch peaks near a gene TSS (promoter-proximal landscape).
    • /tfbs/list/ to list TFs for an assembly with statistics.
    • /stats/ to obtain overall database statistics for an assembly.
    • /tfbs/name/ to fetch peaks for a named TF across cell types.
    • /peaks/biotype/ to fetch peaks filtered by regulatory biotype.
  • When API is unavailable, provides a BED file fallback from https://remap2022.univ-amu.fr/download_page and a Python routine to filter a local BED by region and parse the name field TF:EXPERIMENT_ID:CELL_TYPE.
  • Demonstrates parsing of the peak name field (TF_NAME:EXPERIMENT_ID:CELL_TYPE) and consistent handling of missing parts.
  • Includes example code blocks for region query, gene query, TF list, TF-specific queries, and biotype filtering, with subsequent DataFrame summarization and basic plotting (where code exists).

When to use it

  • You want all TFs with ChIP-seq peaks overlapping a genomic region (e.g., GWAS locus).
  • You need TF peaks near a gene’s TSS to map proximal regulatory landscape.
  • You need a genome-wide list of TFs available in ReMap with peak/dataset counts.
  • You want to download a BED file for a TF across all cell types for offline analysis.
  • You aim to identify co-binding TFs at a locus by querying overlapping peaks and grouping by TF name.
  • You need to use jaspar-database for PWM motifs or encode-database for ENCODE tracks as complementary resources.

What it can touch

  • REST API endpoints under https://remap2022.univ-amu.fr/api/v1 (e.g., peaks/overlap/, peaks/gene/, tfbs/list/, stats/, tfbs/name/, peaks/biotype/).
  • Local BED files downloaded from https://remap2022.univ-amu.fr/download_page when API is unavailable.
  • Python environment with packages: requests, pandas (and matplotlib for optional plots).
  • Examples show parsing and DataFrame generation, including optional BED parsing.

Caveats

  • The skill notes that the ReMap API is a research API and endpoint availability may vary.
  • No explicit authentication is required for the API, but rate limits are not officially published; the samples suggest a slight delay between batch requests (time.sleep(0.5)) to avoid load.
  • BED fallback files are large (e.g., remap2022_all_macs2_hg38_v1_0.bed.gz) and may require substantial disk space.
  • The license listed is CC-BY-4.0 for the skill description, and the repository indicates NOASSERTION for license in the skill metadata, but these are not part of the functional behavior.
From the SKILL.md

# 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-b

What's inside
Steps it walks through
  1. Overview
  2. When to Use
  3. Prerequisites
  4. Quick Start
  5. Core API
  6. Query 1: Region Overlap
  7. Query 2: Gene-Centric Query
  8. Query 3: TF Browser
  9. Query 4: TF-Specific Peak Query
  10. Query 5: Biotype Filter and Regulatory Annotation
  11. Key Concepts
  12. Peak Name Field Format
  13. Assemblies
  14. BED File Download (API Fallback)
Commands it runs
pip install requests pandas matplotlib
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About this skill
What does the remap-database skill do?

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. Use for TF co-occupancy, regulatory annotation, and TF binding atlases. Use jaspar-database for PWM motifs; encode-database for ENCODE tracks.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill remap-database --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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