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dc.contributor.authorOkoniewski, Michal J
dc.contributor.authorMiller, Crispin J
dc.date.accessioned2009-07-07T11:48:59Z
dc.date.available2009-07-07T11:48:59Z
dc.date.issued2006
dc.identifier.citationHybridization interactions between probesets in short oligo microarrays lead to spurious correlations. 2006, 7:276 BMC Bioinformaticsen
dc.identifier.issn1471-2105
dc.identifier.pmid16749918
dc.identifier.doi10.1186/1471-2105-7-276
dc.identifier.urihttp://hdl.handle.net/10541/72756
dc.description.abstractBACKGROUND: Microarrays measure the binding of nucleotide sequences to a set of sequence specific probes. This information is combined with annotation specifying the relationship between probes and targets and used to make inferences about transcript- and, ultimately, gene expression. In some situations, a probe is capable of hybridizing to more than one transcript, in others, multiple probes can target a single sequence. These 'multiply targeted' probes can result in non-independence between measured expression levels. RESULTS: An analysis of these relationships for Affymetrix arrays considered both the extent and influence of exact matches between probe and transcript sequences. For the popular HGU133A array, approximately half of the probesets were found to interact in this way. Both real and simulated expression datasets were used to examine how these effects influenced the expression signal. It was found not only to lead to increased signal strength for the affected probesets, but the major effect is to significantly increase their correlation, even in situations when only a single probe from a probeset was involved. By building a network of probe-probeset-transcript relationships, it is possible to identify families of interacting probesets. More than 10% of the families contain members annotated to different genes or even different Unigene clusters. Within a family, a mixture of genuine biological and artefactual correlations can occur. CONCLUSION: Multiple targeting is not only prevalent, but also significant. The ability of probesets to hybridize to more than one gene product can lead to false positives when analysing gene expression. Comprehensive annotation describing multiple targeting is required when interpreting array data.
dc.language.isoenen
dc.subject.meshArtifacts
dc.subject.meshComputer Simulation
dc.subject.meshDNA Probes
dc.subject.meshData Interpretation, Statistical
dc.subject.meshEquipment Design
dc.subject.meshEquipment Failure
dc.subject.meshEquipment Failure Analysis
dc.subject.meshGene Expression Profiling
dc.subject.meshIn Situ Hybridization
dc.subject.meshModels, Genetic
dc.subject.meshModels, Statistical
dc.subject.meshOligonucleotide Array Sequence Analysis
dc.subject.meshReproducibility of Results
dc.subject.meshSensitivity and Specificity
dc.subject.meshStatistics as Topic
dc.titleHybridization interactions between probesets in short oligo microarrays lead to spurious correlations.en
dc.typeArticleen
dc.contributor.departmentPaterson Institute For Cancer Research, Christie Hospital site, University of Manchester, Wilmslow Road, Manchester, M20 4BX, UK. MOkoniewski@PICR.man.ac.uken
dc.identifier.journalBMC Bioinformaticsen
html.description.abstractBACKGROUND: Microarrays measure the binding of nucleotide sequences to a set of sequence specific probes. This information is combined with annotation specifying the relationship between probes and targets and used to make inferences about transcript- and, ultimately, gene expression. In some situations, a probe is capable of hybridizing to more than one transcript, in others, multiple probes can target a single sequence. These 'multiply targeted' probes can result in non-independence between measured expression levels. RESULTS: An analysis of these relationships for Affymetrix arrays considered both the extent and influence of exact matches between probe and transcript sequences. For the popular HGU133A array, approximately half of the probesets were found to interact in this way. Both real and simulated expression datasets were used to examine how these effects influenced the expression signal. It was found not only to lead to increased signal strength for the affected probesets, but the major effect is to significantly increase their correlation, even in situations when only a single probe from a probeset was involved. By building a network of probe-probeset-transcript relationships, it is possible to identify families of interacting probesets. More than 10% of the families contain members annotated to different genes or even different Unigene clusters. Within a family, a mixture of genuine biological and artefactual correlations can occur. CONCLUSION: Multiple targeting is not only prevalent, but also significant. The ability of probesets to hybridize to more than one gene product can lead to false positives when analysing gene expression. Comprehensive annotation describing multiple targeting is required when interpreting array data.


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