Description
We built a framework to identify tissue-specific functional motifs (funMotifs) across the genome based on thousands of annotation tracks obtained from large-scale genomics projects including ENCODE, RoadMap Epigenomics and FANTOM. The annotations were weighted using a logistic regression model trained on regulatory elements obtained from massively parallel reporter assays. Overall, genome-wide predicted motifs of 519 TFs were characterized across fifteen tissue types. funMotifs summarizes the weighted annotations into a functional activity score for each of the predicted motifs.
Please read the article the data contributed to for further information: https://doi.org/10.1101/683722.
The dataset was originally published in DiVA and moved to SND in 2024.
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| Landing page for the dataset | Unknown | Open resource |