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Accurate prediction of cell type-specific transcription factor binding.

ABSTRACT: Prediction of cell type-specific, in vivo transcription factor binding sites is one of the central challenges in regulatory genomics. Here, we present our approach that earned a shared first rank in the "ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge" in 2017. In post-challenge analyses, we benchmark the influence of different feature sets and find that chromatin accessibility and binding motifs are sufficient to yield state-of-the-art performance. Finally, we provide 682 lists of predicted peaks for a total of 31 transcription factors in 22 primary cell types and tissues and a user-friendly version of our approach, Catchitt, for download.

SUBMITTER: Keilwagen J 

PROVIDER: S-EPMC6327544 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Accurate prediction of cell type-specific transcription factor binding.

Keilwagen Jens J   Posch Stefan S   Grau Jan J  

Genome biology 20190110 1

Prediction of cell type-specific, in vivo transcription factor binding sites is one of the central challenges in regulatory genomics. Here, we present our approach that earned a shared first rank in the "ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge" in 2017. In post-challenge analyses, we benchmark the influence of different feature sets and find that chromatin accessibility and binding motifs are sufficient to yield state-of-the-art performance. Finally, we provid  ...[more]

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