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Virtual ChIP-seq predictions of binding of 36 transcription factor in Roadmap Epigenomics Project tissues

<p>This dataset contains predictions of Virtual ChIP-seq for binding of 36&nbsp;transcription factors in Roadmap Epigenomics dataset tissues with matched DNase-seq and RNA-seq data.</p> <p>Tarball contains subfolders for each of the 36&nbsp;TFs where Virtual ChIP-seq median MCC&nbsp;in validation cell types was &gt; 0.3.</p> <p>Each subfolder contains gzipped BED files. Each file is named as &lt;Tissue&gt;_&lt;Age&gt;_&lt;TF&gt;_&lt;Accession&gt;_Predictions.bed.gz. Columns correspond to Chromosome, Start, End,&nbsp;&lt;Tissue&gt;_&lt;Age&gt;_&lt;TF&gt;_&lt;Accession&gt;, Posterior probability</p> <p>You can use the posterior probabilities provided in Virchip_PosteriorCutoffs_V3.0.0.tsv. These are posterior probability cutoffs which maximized MCC in H1-hESC cell type, or are set to 0.4 if there was no ChIP-seq data of that TF in H1-hESC (0.4 is the mode of all optimal posterior probability cutoffs in H1-hESC).</p>

ShareScore

44/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
20
Reuse readiness
8
Engagement
4

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