We are analyzing https://link.springer.com/article/10.1186/1471-2105-7-276.

Title:
Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations | BMC Bioinformatics
Description:
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
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Keywords {🔍}

probesets, probes, data, correlation, expression, probeset, figure, transcripts, signal, pubmed, article, affymetrix, transcript, probe, file, variance, additional, google, scholar, gene, families, number, intensity, high, spiking, arrays, rma, multiple, array, analysis, matches, effect, targeting, small, low, target, influence, genes, pearson, original, motifs, distribution, cas, filtering, level, database, signals, mas, authors, set,

Topics {✒️}

article download pdf human protein-encoding transcriptomes full size image 1093/nar/gkh036 dai conserved genetic modules org/cgi/content/abstract/101/16/6062] 10 sequence-verified microarray probes efficient real-time rendering sequence-based identification short oligo microarrays robust averaging procedure open software development simple search algorithm family search algorithm privacy choices/manage cookies predict transcript/gene sequences experimental data sources rna expression full access related subjects authors’ original file biomed central gene-transcript-probeset mappings interaction networks implicit nodes represent transcripts pairwise entropy measurements probe-probeset-transcript relationships raw probe intensities short oligo arrays author information authors gene expression measurements molecular biology 2004 sequence-based event sequence based artefacts strict hybridization conditions analyzing microarray data increased measurement accuracy expression-based technologies gene atlas processed gene atlas v2 gene-coexpression network single matching probe cross-species comparisons [7] cdna microarrays [11 european economic area main content log applying algorithmic approaches siani-rose ma childhood acute leukemia ncbi reference sequence

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         headline:Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations
         description: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. 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. 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.
         datePublished:2006-06-02T00:00:00Z
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      headline:Hybridization interactions between probesets in short oligo microarrays lead to spurious correlations
      description: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. 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. 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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         Oligo Array
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         Microarrays
         Computational Biology/Bioinformatics
         Computer Appl. in Life Sciences
         Algorithms
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