Back

HiCHub: A Network-Based Approach to Identify Domains of Differential Interactions from 3D Genome Data

Peng, W.; Yuan, S.; Li, X.; Zhu, S.; Xue, H.

2022-04-17 bioinformatics
10.1101/2022.04.16.488566 bioRxiv
Show abstract

Chromatin architecture is important for gene regulation. Existing algorithms for the identification of interactions changes focus on loops between focal loci. Here we develop a network-based algorithm HiCHub to detect chromatin interaction changes at larger scales. It identifies clusters of genomic elements in physical proximity in one state that exhibit concurrent decreases in interaction among them in the opposite state. The hubs exhibit concordant changes in chromatin state and expression changes, supporting their biological significance. HiCHub works well with data of limited sequencing coverage and facilitates the integration of the one-dimensional epigenetic landscape onto the chromatin architecture. HiCHub provides an approach for finding extended architectural changes and contributes to the connection with transcriptional output. HiCHub is freely available at https://github.com/WeiqunPengLab/HiCHub.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"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.