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/.
| Original language | English |
|---|---|
| Pages (from-to) | 689-694 |
| Number of pages | 6 |
| Journal | Nature Methods |
| Volume | 11 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 2014 |
| Externally published | Yes |
Bibliographical note
Funding Information:T.A.K. thanks J. de Ridder, J. de Ruiter and V. Thorsson for helpful discussions. We thank G. Glusman and H. Dinh for careful reading and commenting on the manuscript. ChIP-seq data was produced by T. Stolyar, G.S. Navarro and C.D. Johnson. T.A.K. thanks H. Rovira and L. Amon for technical assistance. This work was supported by US National Institutes of Health (NIH) grant U54-AI54253, NIH contract HHSN272200700038C from the National Institute of Allergy and Infectious Diseases, NIH NIAID award U19AI100627, NIH NIAID award R01AI025032 to A.A., NIH award K25HL098807 to S.A.R., and NIH award R01HG002939 to A.F.A.S.
