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/.
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Authors | Theo 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 |
Journal | Nature methods
(Nat Methods)
Vol. 11
Issue 6
Pg. 689-94
(Jun 2014)
ISSN: 1548-7105 [Electronic] United States |
PMID | 24727652
(Publication Type: Journal Article, Research Support, N.I.H., Extramural)
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Chemical References |
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Topics |
- Animals
- DNA
(chemistry)
- DNA Methylation
- Genomics
(methods)
- Humans
- Sequence Analysis, DNA
- Software
- Transcriptome
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