Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations.

2.50
Hdl Handle:
http://hdl.handle.net/10541/72756
Title:
Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations.
Authors:
Okoniewski, Michal J; Miller, Crispin J
Abstract:
BACKGROUND: 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.
Affiliation:
Paterson Institute For Cancer Research, Christie Hospital site, University of Manchester, Wilmslow Road, Manchester, M20 4BX, UK. MOkoniewski@PICR.man.ac.uk
Citation:
Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations. 2006, 7:276 BMC Bioinformatics
Journal:
BMC Bioinformatics
Issue Date:
2006
URI:
http://hdl.handle.net/10541/72756
DOI:
10.1186/1471-2105-7-276
PubMed ID:
16749918
Type:
Article
Language:
en
ISSN:
1471-2105
Appears in Collections:
All Paterson Institute for Cancer Research

Full metadata record

DC FieldValue Language
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.en
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

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