We are analyzing https://link.springer.com/article/10.1186/1471-2105-8-108.

Title:
Transcript-based redefinition of grouped oligonucleotide probe sets using AceView: High-resolution annotation for microarrays | BMC Bioinformatics
Description:
Background Extracting biological information from high-density Affymetrix arrays is a multi-step process that begins with the accurate annotation of microarray probes. Shortfalls in the original Affymetrix probe annotation have been described; however, few studies have provided rigorous solutions for routine data analysis. Results Using AceView, a comprehensive human transcript database, we have reannotated the probes by matching them to RNA transcripts instead of genes. Based on this transcript-level annotation, a new probe set definition was created in which every probe in a probe set maps to a common set of AceView gene transcripts. In addition, using artificial data sets we identified that a minimal probe set size of 4 is necessary for reliable statistical summarization. We further demonstrate that applying the new probe set definition can detect specific transcript variants contributing to differential expression and it also improves cross-platform concordance. Conclusion We conclude that our transcript-level reannotation and redefinition of probe sets complement the original Affymetrix design. Redefinitions introduce probe sets whose sizes may not support reliable statistical summarization; therefore, we advocate using our transcript-level mapping redefinition in a secondary analysis step rather than as a replacement. Knowing which specific transcripts are differentially expressed is important to properly design probe/primer pairs for validation purposes. For convenience, we have created custom chip-description-files (CDFs) and annotation files for our new probe set definitions that are compatible with Bioconductor, Affymetrix Expression Console or third party software.
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Keywords {🔍}

probe, set, sets, probes, affymetrix, expression, data, transcript, transcripts, article, gene, pubmed, aceview, figure, google, scholar, original, size, annotation, definition, measurements, method, variants, match, number, mapping, shown, cas, arrays, level, refseq, redefinition, database, genes, newly, central, based, files, genechip, sequence, analysis, bioinformatics, crossplatform, differentially, expressed, defined, authors, results, human, derived,

Topics {✒️}

open access article stochastic-model-based summarization approaches created custom chip-description-files comparing cross-platform data google scholar genome-wide expression profiling representing stearoyl-coa desaturase previous cross-platform analyses /support/technical/manual/expression_manual improves cross-platform concordance high-density oligonucleotide arrays /support/technical/whitepapers/exon_gene_signal_estimate_whitepaper /support/technical/technotes/plier_technote /support/technical/technotes/exon_array_design_technote position-dependent nearest neighbor high-density affymetrix arrays article download pdf genome-wide expression monitoring low cross-platform consistency robust multi-chip-average related subjects model-based-expression indices /support/technical/sample_data/datasets custom chip-description-files cross-platform concordance measured robust expression measurement careful transcript-level annotation full size image utilized gene-level annotations cat=arrays&human] website identical rna samples mecham bh transcript-level mapping redefinition refseq-based probe sets short oligonucleotide microarrays open software development privacy choices/manage cookies jean thierry-mieg acknowledge david wheeler full access intramural research program cross-platform measurements cross-platform comparability biomed central exon-intron boundaries original affymetrix design irizarry ra single transcript variant article lu affymetrix genechips based

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         headline:Transcript-based redefinition of grouped oligonucleotide probe sets using AceView: High-resolution annotation for microarrays
         description:Extracting biological information from high-density Affymetrix arrays is a multi-step process that begins with the accurate annotation of microarray probes. Shortfalls in the original Affymetrix probe annotation have been described; however, few studies have provided rigorous solutions for routine data analysis. Using AceView, a comprehensive human transcript database, we have reannotated the probes by matching them to RNA transcripts instead of genes. Based on this transcript-level annotation, a new probe set definition was created in which every probe in a probe set maps to a common set of AceView gene transcripts. In addition, using artificial data sets we identified that a minimal probe set size of 4 is necessary for reliable statistical summarization. We further demonstrate that applying the new probe set definition can detect specific transcript variants contributing to differential expression and it also improves cross-platform concordance. We conclude that our transcript-level reannotation and redefinition of probe sets complement the original Affymetrix design. Redefinitions introduce probe sets whose sizes may not support reliable statistical summarization; therefore, we advocate using our transcript-level mapping redefinition in a secondary analysis step rather than as a replacement. Knowing which specific transcripts are differentially expressed is important to properly design probe/primer pairs for validation purposes. For convenience, we have created custom chip-description-files (CDFs) and annotation files for our new probe set definitions that are compatible with Bioconductor, Affymetrix Expression Console or third party software.
         datePublished:2007-03-29T00:00:00Z
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      description:Extracting biological information from high-density Affymetrix arrays is a multi-step process that begins with the accurate annotation of microarray probes. Shortfalls in the original Affymetrix probe annotation have been described; however, few studies have provided rigorous solutions for routine data analysis. Using AceView, a comprehensive human transcript database, we have reannotated the probes by matching them to RNA transcripts instead of genes. Based on this transcript-level annotation, a new probe set definition was created in which every probe in a probe set maps to a common set of AceView gene transcripts. In addition, using artificial data sets we identified that a minimal probe set size of 4 is necessary for reliable statistical summarization. We further demonstrate that applying the new probe set definition can detect specific transcript variants contributing to differential expression and it also improves cross-platform concordance. We conclude that our transcript-level reannotation and redefinition of probe sets complement the original Affymetrix design. Redefinitions introduce probe sets whose sizes may not support reliable statistical summarization; therefore, we advocate using our transcript-level mapping redefinition in a secondary analysis step rather than as a replacement. Knowing which specific transcripts are differentially expressed is important to properly design probe/primer pairs for validation purposes. For convenience, we have created custom chip-description-files (CDFs) and annotation files for our new probe set definitions that are compatible with Bioconductor, Affymetrix Expression Console or third party software.
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         Microarrays
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         Computer Appl. in Life Sciences
         Algorithms
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      affiliation:
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               type:PostalAddress
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      affiliation:
            name:National Institute of Standards and Technology
            address:
               name:Chemical Science and Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, USA
               type:PostalAddress
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      affiliation:
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      name:Chemical Science and Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, USA
      name:Genomics Core Laboratory, National Institute of Diabetes & Digestive & Kidney Diseases, National Institutes of Health, Bethesda, USA

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