PT  - JOURNAL ARTICLE
AU  - Florian Schmidt
AU  - Alexander Marx
AU  - Marie Hebel
AU  - Martin Wegner
AU  - Nina Baumgarten
AU  - Manuel Kaulich
AU  - Jonathan Göke
AU  - Jilles Vreeken
AU  - Marcel H. Schulz
TI  - Integrative analysis of epigenetics data identifies gene-specific regulatory elements
AID  - 10.1101/585125
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 585125
4099  - http://biorxiv.org/content/early/2019/03/26/585125.short
4100  - http://biorxiv.org/content/early/2019/03/26/585125.full
AB  - 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.