% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{Okonechnikov:142944,
      author       = {K. Okonechnikov$^*$ and S. Erkek$^*$ and J. O. Korbel and
                      S. Pfister$^*$ and L. Chavez},
      title        = {{I}n{TAD}: chromosome conformation guided analysis of
                      enhancer target genes.},
      journal      = {BMC bioinformatics},
      volume       = {20},
      number       = {1},
      issn         = {1471-2105},
      address      = {Heidelberg},
      publisher    = {Springer},
      reportid     = {DKFZ-2019-00572},
      pages        = {60},
      year         = {2019},
      abstract     = {High-throughput technologies for analyzing chromosome
                      conformation at a genome scale have revealed that chromatin
                      is organized in topologically associated domains (TADs).
                      While TADs are relatively stable across cell types,
                      intra-TAD activities are cell type specific. Epigenetic
                      profiling of different tissues and cell-types has identified
                      a large number of non-coding epigenetic regulatory elements
                      (enhancers) that can be located far away from coding genes.
                      Linear proximity is a commonly chosen criterion for
                      associating enhancers with their potential target genes.
                      While enhancers frequently regulate the closest gene,
                      unambiguous identification of enhancer regulated genes
                      remains to be a challenge in the absence of sample matched
                      chromosome conformation data.To associate enhancers with
                      their target genes, we have previously developed and applied
                      a method that tests for significant correlations between
                      enhancer and gene expressions across a cohort of samples. To
                      limit the number of tests, we constrain this analysis to
                      gene-enhancer pairs embedded in the same TAD, where
                      information on TAD boundaries is borrowed from publicly
                      available chromosome conformation capturing (Hi-C) data. We
                      have now implemented this method as an R Bioconductor
                      package InTAD and verified the software package by
                      reanalyzing available enhancer and gene expression data
                      derived from ependymoma brain tumors.The open-source package
                      InTAD is an easy-to-use software tool for identifying
                      proximal and distal enhancer target genes by leveraging
                      information on correlated expression of enhancers and genes
                      that are located in the same TAD. InTAD can be applied to
                      any heterogeneous cohort of samples analyzed by a
                      combination of gene expression and epigenetic profiling
                      techniques and integrates either public or custom
                      information of TAD boundaries.},
      cin          = {B062},
      ddc          = {610},
      cid          = {I:(DE-He78)B062-20160331},
      pnm          = {312 - Functional and structural genomics (POF3-312)},
      pid          = {G:(DE-HGF)POF3-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:30704404},
      pmc          = {pmc:PMC6357397},
      doi          = {10.1186/s12859-019-2655-2},
      url          = {https://inrepo02.dkfz.de/record/142944},
}