What is UniBind?
UniBind is a comprehensive map of direct transcription factor (TF) – DNA interactions in the human genome. These interactions were obtained uniformly processing thousands of ChIP-seq data sets, from raw reads to high confidence TF binding site predictions, using the ChIP-eat software. The uniform processing, up to ChIP-seq peaks calling was performed by ReMap and the entire collection of ChIP-seq peaks is also available in the ReMap database. ChIP-eat used the MACS2 peak caller to identify ChIP-seq peaks on the hg38 version of the human genome. Next, these genomic regions were analysed with four different TF binding prediction models to derive direct TF-DNA interactions. These models include DiMO-optimized position weight matrices (PWMs), transcription factor flexible models, DNA shape-based models, and binding energy models. An entropy-based algorithm was used to automatically delineate an enrichment zone containing direct TF – DNA interactions, supported by both strong computational evidence and strong experimental evidence. The UniBind database hosts the complete set of TFBS predictions for each prediction model, as well as the models themselves, the original ChIP-seq peaks, and cis-regulatory modules derived from these direct TF – DNA interactions. All the data is publicly available. For further details, please refer to the associated publication: (DOI: https://doi.org/10.1093/nar/gky1210 ).
The data can be searched using the case insensitive search option available on the homepage. The database can be searched for each of the four prediction models, cell/tissue type, and TF name using the ‘Advanced Options’, available on the homepage. Search results are presented in a responsive and paginated table along with metadata information, which can be clicked to view the detail information and download TFBSs, summary plots, and ChIP-seq peaks. All the metadata in the responsive tables can be downloaded as CSV files. The UniBind web interface displays by default the results obtained with the DiMO-optimized PWMs but results obtained from all TFBS computational models along with the trained models are available for browsing and/or download.
The UniBind web interface was developed in Python using the model-view-controller framework Django. It uses MySQL to store TFBS metadata and Bootstrap as the frontend template engine. The source code is available at https://bitbucket.org/CBGR/unibind.
Cell lines & Tissues