Predicted cis-regulatory modules and their binding sites
CRMs and transcription factor binding sites predicted from public TF ChIP-seq data for human and mouse. Fruit fly, worm and thale cress are coming soon.
- Human CRMs (v2) 1,426,947
- Mouse CRMs (v2) 912,197
- D. melanogaster CRMs (v1) Coming soon
- C. elegans CRMs (v1) Coming soon
- A. thaliana CRMs (v1) Coming soon
How the predictions are made
dePCRM2 on GitHubPCRMs uses dePCRM2, which predicts CRMs from transcription factor (TF) ChIP-seq data alone, with no histone marks or other epigenetic data. It finds TF motifs that repeatedly occur together across thousands of TF ChIP-seq datasets and links their binding sites into cis-regulatory modules.
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Step A: Extend binding peaks
Each TF ChIP-seq binding peak in every dataset is extended at both ends to 1,000 bp, so nearby sites of cooperating TFs are included.
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Step B: Find motifs
ProSampler finds the motifs in each dataset; each shape is a different motif.
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Step C: Find co-occurring pairs
Pairs of motifs that repeatedly occur together in the same peaks are identified in each dataset.
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Step D: Merge into unique motifs
Similar motifs from different datasets are clustered into unique motifs (UMs), each likely bound by one TF or TF family.
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Step E: Build interaction networks
Unique motifs that tend to co-occur are connected, giving a network of cooperating TFs.
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Step F: Link adjacent binding sites
Binding sites are mapped back to the genome and neighbouring sites are linked into CRM candidates (CRMCs).
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Step G: Score and filter
Each candidate gets an SCRM score and p-value. Candidates that pass the p-value cutoff are the predicted CRMs in PCRMs.
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Browse the CRM maps
Result: predicted CRMs
The CRMs that pass the cutoff, with their binding sites, make up the maps in PCRMs.
Cite PCRMs
Ni P, Su Z. PCRMS: a database of predicted cis-regulatory modules and constituent transcription factor binding sites in genomes. Database 2022; baac024. doi:10.1093/database/baac024