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dc.contributor.authorChen, Yiwen
dc.contributor.authorMeyer, Clifford
dc.contributor.authorLiu, Tao
dc.contributor.authorLi, Wei
dc.contributor.authorLiu, Jun
dc.contributor.authorLiu, Xiaole (Shirley) Shirley
dc.date.accessioned2016-05-13T18:37:37Z
dc.date.issued2011
dc.identifier.citationChen, Yiwen, Clifford A Meyer, Tao Liu, Wei Li, Jun S Liu, and Xiaole Shirley Liu. 2011. “MM-ChIP Enables Integrative Analysis of Cross-Platform and Between-Laboratory ChIP-Chip or ChIP-Seq Data.” Genome Biology 12 (2): R11. doi:10.1186/gb-2011-12-2-r11.en_US
dc.identifier.issn1465-6906en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:27002573
dc.description.abstractThe ChIP-chip and ChIP-seq techniques enable genome-wide mapping of in vivo protein-DNA interactions and chromatin states. The cross-platform and between-laboratory variation poses a challenge to the comparison and integration of results from different ChIP experiments. We describe a novel method, MM-ChIP, which integrates information from cross-platform and between-laboratory ChIP-chip or ChIP-seq datasets. It improves both the sensitivity and the specificity of detecting ChIP-enriched regions, and is a useful meta-analysis tool for driving discoveries from multiple data sources.en_US
dc.language.isoen_USen_US
dc.publisherSpringer Science + Business Mediaen_US
dc.relation.isversionofdoi:10.1186/gb-2011-12-2-r11en_US
dash.licenseLAA
dc.titleMM-ChIP enables integrative analysis of cross-platform and between-laboratory ChIP-chip or ChIP-seq dataen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalGenome Biolen_US
dash.depositing.authorLiu, Jun
dc.date.available2016-05-13T18:37:37Z
dc.identifier.doi10.1186/gb-2011-12-2-r11*
dash.authorsorderedfalse
dash.contributor.affiliatedLiu, Tao
dash.contributor.affiliatedChen, Yiwen
dash.contributor.affiliatedMeyer, Clifford
dash.contributor.affiliatedLiu, Xiaole
dash.contributor.affiliatedLiu, Jun


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