TY  - INPR
A1  - Hoffmann, Markus
A1  - Trummer, Nico
A1  - Schwartz, Leon
A1  - Jankowski, Jakub
A1  - Kyung Lee, Hye
A1  - Willruth, Lina-Liv
A1  - Lazareva, Olga
A1  - Yuan, Kevin
A1  - Baumgarten, Nina
A1  - Schmidt, Florian
A1  - Baumbach, Jan
A1  - Schulz, Marcel Holger
A1  - Blumenthal, David B.
A1  - Hennighausen, Lothar
A1  - List, Markus
T1  - TF-Prioritizer: a java pipeline to prioritize condition-specific transcription factors
T2  - bioRxiv
N2  - Background: Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results.
Results: We developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences.
Conclusion: TF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.
Y1  - 2023
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/75586
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-755860
UR  - https://www.biorxiv.org/content/10.1101/2022.10.19.512881v2
IS  - 2022.10.19.512881 Version 2
ER  -