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Multiscale representation of genomic signals.

Abstract
Genomic information is encoded on a wide range of distance scales, ranging from tens of bases to megabases. We developed a multiscale framework to analyze and visualize the information content of genomic signals. Different types of signals, such as G+C content or DNA methylation, are characterized by distinct patterns of signal enrichment or depletion across scales spanning several orders of magnitude. These patterns are associated with a variety of genomic annotations. By integrating the information across all scales, we demonstrated improved prediction of gene expression from polymerase II chromatin immunoprecipitation sequencing (ChIP-seq) measurements, and we observed that gene expression differences in colorectal cancer are related to methylation patterns that extend beyond the single-gene scale. Our software is available at https://github.com/tknijnen/msr/.
AuthorsTheo A Knijnenburg, Stephen A Ramsey, Benjamin P Berman, Kathleen A Kennedy, Arian F A Smit, Lodewyk F A Wessels, Peter W Laird, Alan Aderem, Ilya Shmulevich
JournalNature methods (Nat Methods) Vol. 11 Issue 6 Pg. 689-94 (Jun 2014) ISSN: 1548-7105 [Electronic] United States
PMID24727652 (Publication Type: Journal Article, Research Support, N.I.H., Extramural)
Chemical References
  • DNA
Topics
  • Animals
  • DNA (chemistry)
  • DNA Methylation
  • Genomics (methods)
  • Humans
  • Sequence Analysis, DNA
  • Software
  • Transcriptome

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