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• W2339656649 abstract "Abstract Motivation: Computational prediction of transcription factor (TF) binding sites in the genome remains a challenging task. Here, we present Romulus, a novel computational method for identifying individual TF binding sites from genome sequence information and cell-type–specific experimental data, such as DNase-seq. It combines the strengths of previous approaches, and improves robustness by reducing the number of free parameters in the model by an order of magnitude. Results: We show that Romulus significantly outperforms existing methods across three sources of DNase-seq data, by assessing the performance of these tools against ChIP-seq profiles. The difference was particularly significant when applied to binding site prediction for low-information-content motifs. Our method is capable of inferring multiple binding modes for a single TF, which differ in their DNase I cut profile. Finally, using the model learned by Romulus and ChIP-seq data, we introduce Binding in Closed Chromatin (BCC) as a quantitative measure of TF pioneer factor activity. Uniquely, our measure quantifies a defining feature of pioneer factors, namely their ability to bind closed chromatin. Availability and Implementation: Romulus is freely available as an R package at http://github.com/ajank/Romulus . Contact: ajank@mimuw.edu.pl Supplementary information: Supplementary data are available at Bioinformatics online." @default.
• W2339656649 created "2016-06-24" @default.
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• W2339656649 date "2016-04-19" @default.
• W2339656649 modified "2023-09-24" @default.
• W2339656649 title "Romulus: robust multi-state identification of transcription factor binding sites from DNase-seq data" @default.
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• W2339656649 doi "https://doi.org/10.1093/bioinformatics/btw209" @default.
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