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Virtual ChIP-seq predictions of binding of 34 transcription factor in Roadmap Epigenomics Project tissues

Research datakeyboard_double_arrow_right Dataset 01 Mar 2018Publisher:Zenodo

Authors: Mehran Karimzadeh; Michael M. Hoffman;

doi: 10.5281/zenodo.1066932

Virtual ChIP-seq predictions of binding of 34 transcription factor in Roadmap Epigenomics Project tissues

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Abstract

This dataset contains predictions of Virtual ChIP-seq for binding of 34 transcription factors in Roadmap Epigenomics dataset tissues with matched DNase-seq and RNA-seq data. Tarball contains subfolders for each of the 34 TFs where Virtual ChIP-seq median MCC in validation cell types was > 0.3. Each subfolder contains gzipped BED files. Each file is named as ____Predictions.bed.gz. Columns correspond to Chromosome, Start, End, ___, Posterior probability You can use the posterior probabilities provided in Virchip_PosteriorCutoffs.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).

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University of Toronto
Canada

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Virtual ChIP-seq

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Virtual Chip-Seq Predictions Of Binding Of 36 Transcription Factor In Roadmap Epigenomics Project Tissues

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Virtual Chip-Seq Predictions Of Binding Of 36 Transcription Factor In Roadmap Epigenomics Project Tissues

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Virtual ChIP-seq predictions of binding of 31 transcription factor in Roadmap Epigenomics Project tissues

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