The transcriptional regulation of genes is a highly complex process, requiring the precisely timed activation of transcription factors (TFs), enhancers or repressors. We still don't completely understand this process, though recent technological advances provide more and deeper insight into the mechanisms involved in transcriptional regulation. These include techniques to observe TF/enhancer binding to DNA, modification of histones and DNA, opening or closing of the DNA-structure, as well as larger-scale structural re-organization of the DNA.

One key step for computational biologists is to analyze and interpret these epigenetic and TF occupancy data. This includes the annotation of these epigenetic and occupancy data with genomic features, with each other, as well as with available data on gene expression dynamics.

AnnoMiner: integrating epigenetic and transcription factor occupancy and transcriptomic data to predict transcriptional regulators

The 4 AnnoMiner function: peak annotation, peak integration, nearby gene annotation and TF enrichment analysis.

With AnnoMiner, we provide a web-platform that allows to annotate and integrate epigenetic and TF occupancy data with genomic features and with each other. Optionally, the user can also integrate gene expression data, enabling the identification of potential direct targets of on, or of a combination of transcriptional regulators. Gene features are divided into upstream/downstream regions, transcription start site (TSS) untranslated regions, as well as the coding region; from a graphical 'coverage plot' that shows the overlap of a transcriptional regulator under study with these regions, the user can choose which region is most interesting to him for subsequent annotation.

AnnoMiner also allows to mine 10 nearby genes to a TF peak of genomic variant, with the nearby gene function. For this function, a single peak or region can be submitted, in combination with a list of differentially expressed genes. The 5 upstream and downstream genes to the peak will be visualized, together with information on their de-regulation.

Finally, AnnoMiner can be used to annotate a list of differentially expressed genes to look for transcription factors whose peaks are enriched in the submitted list.