TY  - INPR
A1  - Schmidt, Florian
A1  - Marx, Alexander
A1  - Hebel, Marie
A1  - Wegner, Martin
A1  - Baumgarten, Nina
A1  - Kaulich, Manuel
A1  - Göke, Jonathan
A1  - Vreeken, Jilles
A1  - Schulz, Marcel Holger
T1  - Integrative analysis of epigenetics data identifies gene-specific regulatory elements
T2  - bioRxiv
N2  - Understanding the complexity of transcriptional regulation is a major goal of computational biology. Because experimental linkage of regulatory sites to genes is challenging, computational methods considering epigenomics data have been proposed to create tissue-specific regulatory maps. However, we showed that these approaches are not well suited to account for the variations of the regulatory landscape between cell-types. To overcome these drawbacks, we developed a new method called STITCHIT, that identifies and links putative regulatory sites to genes. Within STITCHIT, we consider the chromatin accessibility signal of all samples jointly to identify regions exhibiting a signal variation related to the expression of a distinct gene. STITCHIT outperforms previous approaches in various validation experiments and was used with a genome-wide CRISPR-Cas9 screen to prioritize novel doxorubicin-resistance genes and their associated non-coding regulatory regions. We believe that our work paves the way for a more refined understanding of transcriptional regulation at the gene-level.
Y1  - 2019
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/72540
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-725409
UR  - https://www.biorxiv.org/content/10.1101/585125v1
IS  - 585125 Version 1
PB  - bioRxiv
ER  -