Epilogos: information-theoretic navigation of multi-tissue functional genomic annotations
Quon, J.; Reynolds, A. P.; Tripician, N.; Rynes, E. T.; Teodosiadis, A.; Kellis, M.; Meuleman, W.
Show abstract
Functional genomics data, such as chromatin state maps, provide critical insights into biological processes, but are hard to navigate and interpret. We present Epilogos to address this challenge by offering a simple information-theoretic framework for large-scale visualization, navigation and interpretation of functional genomics annotations, and apply it to over 2,000 genome-wide chromatin state maps in human and mouse. We construct intuitive visualizations of multi-tissue chromatin state maps, prioritize salient genomic regions, identify group-wise differential regions, and enable rapid similarity search given a region of interest. To facilitate usability, we provide a purpose-built web-based browser interface (http://epilogos.net) alongside open-source software for community access and adoption.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- SnapATAC: A Comprehensive Analysis Package for Single Cell ATAC-seq 97%
- Boosting the detection of enhancer-promoter loops via novel normalization methods for chromatin interaction data 97%
- Fine-mapping of nuclear compartments using ultra-deep Hi-C shows that active promoter and enhancer elements localize in the active A compartment even when adjacent sequences do not 96%
Similar papers in this journal
Similar papers in this journal
- Sequence-based modeling of genome 3D architecture from kilobase to chromosome-scale 98%
- ChIP-DIP: A multiplexed method for mapping hundreds of proteins to DNA uncovers diverse regulatory elements controlling gene expression 96%
- Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings 96%
Similar papers in this journal
- Dictionary learning for integrative, multimodal, and scalable single-cell analysis 96%
- Multi-omics integration and regulatory inference for unpaired single-cell data with a graph-linked unified embedding framework 96%
- Quantitative single cell 5hmC sequencing reveals non-canonical gene regulation by non-CG hydroxymethylation 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.