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dc.contributor.authorLiu, Fang
dc.contributor.authorJenssen, Tor-Kristian
dc.contributor.authorTrimarchi, Jeff
dc.contributor.authorPunzo, Claudio
dc.contributor.authorCepko, Connie L
dc.contributor.authorOhno-Machado, Lucila
dc.contributor.authorHovig, Eivind
dc.contributor.authorPatrick Kuo, Winston
dc.date.accessioned2015-10-09T01:24:02Z
dc.date.available2015-10-09T01:24:02Z
dc.date.issued2007
dc.identifier.citationBMC Genomics. 2007 Jun 07;8(1):153
dc.identifier.urihttp://hdl.handle.net/10852/46478
dc.description.abstractBackground High-throughput systems for gene expression profiling have been developed and have matured rapidly through the past decade. Broadly, these can be divided into two categories: hybridization-based and sequencing-based approaches. With data from different technologies being accumulated, concerns and challenges are raised about the level of agreement across technologies. As part of an ongoing large-scale cross-platform data comparison framework, we report here a comparison based on identical samples between one-dye DNA microarray platforms and MPSS (Massively Parallel Signature Sequencing). Results The DNA microarray platforms generally provided highly correlated data, while moderate correlations between microarrays and MPSS were obtained. Disagreements between the two types of technologies can be attributed to limitations inherent to both technologies. The variation found between pooled biological replicates underlines the importance of exercising caution in identification of differential expression, especially for the purposes of biomarker discovery. Conclusion Based on different principles, hybridization-based and sequencing-based technologies should be considered complementary to each other, rather than competitive alternatives for measuring gene expression, and currently, both are important tools for transcriptome profiling.
dc.language.isoeng
dc.rightsLiu et al.
dc.rightsAttribution 2.0 Generic
dc.rights.urihttp://creativecommons.org/licenses/by/2.0/
dc.titleComparison of hybridization-based and sequencing-based gene expression technologies on biological replicates
dc.typeJournal article
dc.date.updated2015-10-09T01:24:02Z
dc.creator.authorLiu, Fang
dc.creator.authorJenssen, Tor-Kristian
dc.creator.authorTrimarchi, Jeff
dc.creator.authorPunzo, Claudio
dc.creator.authorCepko, Connie L
dc.creator.authorOhno-Machado, Lucila
dc.creator.authorHovig, Eivind
dc.creator.authorPatrick Kuo, Winston
dc.identifier.doihttp://dx.doi.org/10.1186/1471-2164-8-153
dc.identifier.urnURN:NBN:no-50669
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/46478/1/12864_2006_Article_866.pdf
dc.type.versionPublishedVersion
cristin.articleid153


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