Knowledge integration for analyzing ChIP-seq

Deyu Zhou, Yulan He

Research output: Contribution to journalArticle

Abstract

To capture the genomic profiles for histone modification, chromatin immunoprecipitation (ChIP) is combined with next generation sequencing, which is called ChIP-seq. However, enriched regions generated from the ChIP-seq data are only evaluated on the limited knowledge acquired from manually examining the relevant biological literature. This paper proposes a novel framework, which integrates multiple knowledge sources such as biological literature, Gene Ontology, and microarray data. In order to precisely analyze ChIP-seq data for histone modification, knowledge integration is based on a unified probabilistic model. The model is employed to re-rank the enriched regions generated from peak finding algorithms. Through filtering the reranked enriched regions using some predefined threshold, more reliable and precise results could be generated. The combination of the multiple knowledge sources with the peaking finding algorithm produces a new paradigm for ChIP-seq data analysis.
Original languageEnglish
Pages (from-to)1344-1348
Number of pages5
JournalAdvanced Materials Research
Volume532-533
DOIs
Publication statusPublished - 2012

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Microarrays
Ontology
Genes
Statistical Models

Keywords

  • ChIP-seq
  • microarray
  • knowledge integration
  • histone modification
  • gene ontology

Cite this

Zhou, Deyu ; He, Yulan. / Knowledge integration for analyzing ChIP-seq. In: Advanced Materials Research. 2012 ; Vol. 532-533. pp. 1344-1348.
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Knowledge integration for analyzing ChIP-seq. / Zhou, Deyu; He, Yulan.

In: Advanced Materials Research, Vol. 532-533, 2012, p. 1344-1348.

Research output: Contribution to journalArticle

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