TitleMultiscale representation of genomic signals.
Publication TypeJournal Article
Year of Publication2014
AuthorsKnijnenburg, TA, Ramsey, SA, Berman, BP, Kennedy, KA, Smit, AFA, Wessels, LFA, Laird, PW, Aderem, A, Shmulevich, I
JournalNat Methods
Volume11
Issue6
Pagination689-94
Date Published2014 Jun
ISSN1548-7105
KeywordsAnimals, DNA, DNA Methylation, Genomics, Humans, Sequence Analysis, DNA, Software, Transcriptome
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/.

DOI10.1038/nmeth.2924
Alternate JournalNat Methods
PubMed ID24727652
PubMed Central IDPMC4040162
Grant ListU24 CA143882 / CA / NCI NIH HHS / United States
HHSN272200700038C / / PHS HHS / United States
R01HG002939 / HG / NHGRI NIH HHS / United States
U19 AI100627 / AI / NIAID NIH HHS / United States
R01 HG002939 / HG / NHGRI NIH HHS / United States
R01AI025032 / AI / NIAID NIH HHS / United States
R01 AI025032 / AI / NIAID NIH HHS / United States
U54-AI54253 / AI / NIAID NIH HHS / United States
U19AI100627 / AI / NIAID NIH HHS / United States
HHSN272200700038C / AI / NIAID NIH HHS / United States
K25HL098807 / HL / NHLBI NIH HHS / United States
K25 HL098807 / HL / NHLBI NIH HHS / United States