Chipatlas Tools

Configuration File: chipatlas_tools.json Tool Type: Local Tools Count: 7

This page contains all tools defined in the chipatlas_tools.json configuration file.

Available Tools

ChIPAtlas_enrichment_analysis (Type: ChIPAtlasTool)

NON-FUNCTIONAL / stub (checked 2026-09-22): ChIP-Atlas’s enrichment analysis (identifying transcr…

ChIPAtlas_enrichment_analysis tool specification

Tool Information:

• Name: ChIPAtlas_enrichment_analysis

• Type: ChIPAtlasTool

• Description: NON-FUNCTIONAL / stub (checked 2026-09-22): ChIP-Atlas’s enrichment analysis (identifying transcription factors enriched in a set of BED regions, a motif, or a gene list) is only available as a JavaScript web form at chip-atlas.org/enrichment_analysis with no REST/CGI endpoint behind it; this tool does not call it and cannot rank or score anything. Whatever input you give (bed_data, motif, or gene_list), it returns a fixed instructional message plus the submission URL and your echoed parameters – ‘genome’ and every other filter are accepted but have no effect on the response, which is identical regardless of their value. For the one direction ChIP-Atlas does expose programmatically – given a transcription factor, its ranked target genes – use ChIPAtlas_get_target_genes instead.

Parameters:

• operation (string) (optional) No description

• bed_data (string) (optional) Option 1: BED format genomic regions (tab-separated: chr, start, end). For finding proteins bound to specific genomic regions. Example: ‘chr1t1000t2000nchr2t3000t4000’.

• motif (string) (optional) Option 2: DNA sequence motif in IUPAC notation. Use: A/T/G/C (bases), W=A|T, S=G|C, M=A|C, K=G|T, R=A|G, Y=C|T, B=C|G|T, D=A|G|T, H=A|C|T, V=A|C|G, N=any. For finding proteins bound to specific DNA sequences. Example: ‘CANNTG’ (E-box motif).

• gene_list ([‘array’, ‘string’]) (optional) Option 3: Gene symbols (HGNC for human, MGI for mouse, RGD for rat, FlyBase, WormBase, SGD for yeast). Provide as array or single gene. For finding transcription factors regulating genes. Example: [‘TP53’, ‘MDM2’, ‘CDKN1A’].

• genome (string) (optional) Genome assembly

• antigen_class (string) (optional) Filter by antigen class (e.g., ‘TFs and others’, ‘Histone’, ‘RNA polymerase’)

• cell_type_class (string) (optional) Filter by cell type class (e.g., ‘Blood’, ‘Liver’, ‘Brain’)

• threshold (string) (optional) Peak calling stringency (MACS2 Q-value). Options: ‘05’=1e-5 (permissive, more peaks, broader features), ‘10’=1e-10 (moderate, balanced), ‘20’=1e-20 (strict, high confidence only, narrow peaks). Default ‘05’ suitable for most analyses. Higher values = fewer but more confident peaks.

• distance (string) (optional) Distance from Transcription Start Site (TSS) in base pairs for gene-TF association. Defines promoter region. Default 5000 (±5kb, captures typical promoters). Use 1000-2000 for narrow promoters, 10000+ for enhancer regions.

Example Usage:

query = {
    "name": "ChIPAtlas_enrichment_analysis",
    "arguments": {
    }
}
result = tu.run(query)

ChIPAtlas_get_colocalization (Type: ChIPAtlasTool)

ChIP-Atlas colocalization partners ranked by genome-wide overlap score. Results are recoverably p…

ChIPAtlas_get_colocalization tool specification

Tool Information:

• Name: ChIPAtlas_get_colocalization

• Type: ChIPAtlasTool

• Description: ChIP-Atlas colocalization partners ranked by genome-wide overlap score. Results are recoverably paginated: start with offset=0 and continue with data.next_offset while data.has_more is true; data.partner_count is the complete count.

Parameters:

• operation (string) (optional) No description

• antigen (string) (required) Antigen / transcription factor symbol (e.g. ‘CTCF’, ‘AFF4’).

• cell_type_class (string) (required) Tissue / cell-type class for which the colocalization matrix was computed (e.g. ‘Blood’, ‘Breast’, ‘Liver’, ‘Digestive tract’). Spaces are allowed.

• genome (string) (optional) Genome assembly.

• limit (integer) (optional) Maximum number of ranked partner proteins to return.

• offset (integer) (optional) Zero-based ranked-partner offset. Continue with data.next_offset.

Example Usage:

query = {
    "name": "ChIPAtlas_get_colocalization",
    "arguments": {
        "antigen": "example_value",
        "cell_type_class": "example_value"
    }
}
result = tu.run(query)

ChIPAtlas_get_experiment_metadata (Type: ChIPAtlasTool)

ChIP-Atlas single-experiment structured metadata: given one experiment accession (SRX/DRX/ERX), r…

ChIPAtlas_get_experiment_metadata tool specification

Tool Information:

• Name: ChIPAtlas_get_experiment_metadata

• Type: ChIPAtlasTool

• Description: ChIP-Atlas single-experiment structured metadata: given one experiment accession (SRX/DRX/ERX), return its antigen class and antigen, cell-type class and cell type, title, and the full parsed sample attributes (antibody, source, cell line, etc.). One accession can map to multiple genome assemblies; filter with the optional ‘genome’ parameter. Use for: resolving what an SRX experiment actually measured, looking up the antibody/cell line behind a peak set, validating experiment IDs returned by other ChIP-Atlas tools.

Parameters:

• operation (string) (optional) No description

• experiment_id (string) (required) Experiment accession in SRX/DRX/ERX format (e.g. ‘SRX080331’).

• genome (string) (optional) Optional: restrict to one genome assembly (an experiment can have records for several, e.g. hg38 and hg19).

Example Usage:

query = {
    "name": "ChIPAtlas_get_experiment_metadata",
    "arguments": {
        "experiment_id": "example_value"
    }
}
result = tu.run(query)

ChIPAtlas_get_experiments (Type: ChIPAtlasTool)

Search ChIP-Atlas experiment metadata including experiment IDs, antigens, cell types, and process…

ChIPAtlas_get_experiments tool specification

Tool Information:

• Name: ChIPAtlas_get_experiments

• Type: ChIPAtlasTool

• Description: Search ChIP-Atlas experiment metadata including experiment IDs, antigens, cell types, and processing statistics. Filter by genome, antigen (TF/histone), or cell type. Returns experiment details with SRX/ERX/DRX IDs. Use for: finding relevant experiments, getting experiment metadata, dataset discovery, batch analysis planning.

Parameters:

• operation (string) (optional) No description

• genome (string) (optional) Filter by genome assembly

• antigen (string) (optional) Filter by antigen/protein name (e.g., ‘CTCF’, ‘H3K4me3’)

• cell_type (string) (optional) Filter by cell type (e.g., ‘K-562’, ‘HepG2’, ‘CD4’)

• limit (integer) (optional) Maximum results to return

Example Usage:

query = {
    "name": "ChIPAtlas_get_experiments",
    "arguments": {
    }
}
result = tu.run(query)

ChIPAtlas_get_peak_data (Type: ChIPAtlasTool)

Get download URLs for ChIP-Atlas peak-call data in BigWig, BED, or BigBed format. BigWig contains…

ChIPAtlas_get_peak_data tool specification

Tool Information:

• Name: ChIPAtlas_get_peak_data

• Type: ChIPAtlasTool

• Description: Get download URLs for ChIP-Atlas peak-call data in BigWig, BED, or BigBed format. BigWig contains coverage scores in RPM (Reads Per Million). BED/BigBed contain peak regions with MACS2 (Model-based Analysis of ChIP-Seq) peak caller scores. Use for: downloading raw data, integrating with genome browsers (UCSC, IGV), custom analysis, visualization.

Parameters:

• operation (string) (optional) No description

• experiment_id (string) (required) Experiment ID (SRX/ERX/DRX format, required)

• genome (string) (optional) Genome assembly

• format (string) (optional) Output format

• threshold (string) (optional) Q-value threshold for BED/BigBed peak files. ‘05’=1e-5 (more peaks), ‘10’=1e-10 (moderate), ‘20’=1e-20 (high confidence only). Only applies to BED/BigBed formats. Default ‘05’.

Example Usage:

query = {
    "name": "ChIPAtlas_get_peak_data",
    "arguments": {
        "experiment_id": "example_value"
    }
}
result = tu.run(query)

ChIPAtlas_get_target_genes (Type: ChIPAtlasTool)

ChIP-Atlas transcription-factor target genes ranked by average TSS-proximal binding score. Result…

ChIPAtlas_get_target_genes tool specification

Tool Information:

• Name: ChIPAtlas_get_target_genes

• Type: ChIPAtlasTool

• Description: ChIP-Atlas transcription-factor target genes ranked by average TSS-proximal binding score. Results are recoverably paginated: start with offset=0 and continue with data.next_offset while data.has_more is true; data.gene_count is the complete count.

Parameters:

• operation (string) (optional) No description

• antigen (string) (required) Transcription factor / antigen symbol (e.g. ‘GATA1’, ‘CTCF’).

• genome (string) (optional) Genome assembly.

• distance (string) (optional) TSS-distance window in kb defining ‘bound near a gene’. ‘1’ (±1kb, strict promoter), ‘5’ (±5kb, default), ‘10’ (±10kb, includes nearby enhancers).

• limit (integer) (optional) Maximum number of top-scoring target genes to return.

• offset (integer) (optional) Zero-based ranked-gene offset. Continue with data.next_offset.

Example Usage:

query = {
    "name": "ChIPAtlas_get_target_genes",
    "arguments": {
        "antigen": "example_value"
    }
}
result = tu.run(query)

ChIPAtlas_search_datasets (Type: ChIPAtlasTool)

Search ChIP-Atlas by exactly one of antigen or cell type. Matching metadata rows and the experime…

ChIPAtlas_search_datasets tool specification

Tool Information:

• Name: ChIPAtlas_search_datasets

• Type: ChIPAtlasTool

• Description: Search ChIP-Atlas by exactly one of antigen or cell type. Matching metadata rows and the experiment IDs inside each row are both recoverably paginated: continue outer rows with data.next_offset, and continue IDs with each result’s next_experiment_id_offset. Counts are complete, so a short experiment_ids list must not be interpreted as the full dataset.

Parameters:

• operation (string) (optional) No description

• antigen (string) (optional) Search by antigen/protein name (e.g., ‘CTCF’, ‘H3K27ac’)

• cell_type (string) (optional) Search by cell type (e.g., ‘K-562’, ‘HeLa’, ‘MCF-7’)

• genome (string) (optional) Genome assembly

• limit (integer) (optional) Maximum number of matching antigen/cell-type rows to return.

• offset (integer) (optional) Zero-based offset into matching antigen/cell-type rows. Continue with data.next_offset.

• experiment_id_limit (integer) (optional) Maximum experiment IDs returned inside each matching row.

• experiment_id_offset (integer) (optional) Zero-based experiment-ID offset applied inside each returned row. Repeat the same row page with each result’s next_experiment_id_offset until experiment_ids_have_more is false.

Example Usage:

query = {
    "name": "ChIPAtlas_search_datasets",
    "arguments": {
    }
}
result = tu.run(query)

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