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)

Perform enrichment analysis to identify transcription factors and histone modifications enriched …

ChIPAtlas_enrichment_analysis tool specification

Tool Information:

• Name: ChIPAtlas_enrichment_analysis

• Type: ChIPAtlasTool

• Description: Perform enrichment analysis to identify transcription factors and histone modifications enriched in your data. Required: Provide ONE input type - (1) BED genomic regions, (2) DNA sequence motif (IUPAC notation: A/T/G/C/W/S/M/K/R/Y/B/D/H/V/N), or (3) gene symbol list. Compares your input against 433,000+ ChIP-seq/ATAC-seq/Bisulfite-seq experiments to identify significant enrichment. Returns ranked list of proteins bound to your regions/motif or regulating your genes. Note: Returns submission URL (web form-based analysis). Use for: identifying regulators of genomic regions, finding proteins bound to sequence motifs, discovering transcription factors regulating gene sets.

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: for a given antigen/transcription factor in a specific tissue class, r…

ChIPAtlas_get_colocalization tool specification

Tool Information:

• Name: ChIPAtlas_get_colocalization

• Type: ChIPAtlasTool

• Description: ChIP-Atlas Colocalization: for a given antigen/transcription factor in a specific tissue class, return the other proteins whose ChIP-seq peaks co-occur (co-bind) genome-wide, ranked by overlap score. Reveals protein complexes and co-regulators (e.g. CTCF in Blood co-binds the cohesin subunits RAD21, SMC1A, SMC3, STAG1 and ZNF143). Requires both an antigen and a cell-type/tissue class because the matrix is precomputed per antigen-per-tissue. To discover which tissue classes exist for an antigen, consult the index at https://chip-atlas.org/data/colo_analysis.json?genome=<genome>. Use for: identifying co-binding partners, inferring TF complexes, finding co-regulators of a factor in a tissue.

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.

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 Target Genes: for a transcription factor, return its ranked list of potential target g…

ChIPAtlas_get_target_genes tool specification

Tool Information:

• Name: ChIPAtlas_get_target_genes

• Type: ChIPAtlasTool

• Description: ChIP-Atlas Target Genes: for a transcription factor, return its ranked list of potential target genes - genes whose TSS-proximal region is bound by the TF - scored as the average binding strength across all ChIP-seq experiments for that TF. Choose the TSS-distance window with the ‘distance’ parameter (1, 5, or 10 kb). Use for: predicting which genes a TF regulates, building TF-target gene sets, prioritizing direct targets. To check which TFs have target-gene data for a genome, see https://chip-atlas.org/data/target_genes_analysis.json. Note: a few antigens (including CTCF on hg38) are served with a header but no scored rows; in that case the tool returns gene_count 0 with an explanatory note - pick another factor (e.g. ‘GATA1’).

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.

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 antigen or cell type to find available datasets. Returns number of experimen…

ChIPAtlas_search_datasets tool specification

Tool Information:

• Name: ChIPAtlas_search_datasets

• Type: ChIPAtlasTool

• Description: Search ChIP-Atlas by antigen or cell type to find available datasets. Returns number of experiments and experiment IDs. Use antigenList for finding TF/histone datasets across cell types. Use celltypeList for finding all factors in specific cell type. Use for: dataset discovery, planning comparative analysis, checking data availability.

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

Example Usage:

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

Navigation

• Available Tools - Back to Tools Overview

• Tool Loading Tutorial - Loading Local Tools