Evidence map›Paper›PMID 17394657›Full record

ArticleBMC bioinformatics2007

Transcript-based redefinition of grouped oligonucleotide probe sets using AceView: high-resolution annotation for microarrays.

Jun Lu, Joseph C Lee, Marc L Salit, Margaret C Cam

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Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

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37citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

37 citing papers in PubMed.

  1. GEO dataset mining analysis reveals novelFrontiers in molecular biosciences · 2024
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  3. Data MiningInternational journal of genomics · 2018
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  7. Introduction to sequencing the brain transcriptome.International review of neurobiology · 2014
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  9. Genes, behavior and next-generation RNA sequencing.Genes, brain, and behavior · 2013
    Review
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Jun LuGenomics Core Laboratory, National Institute of Diabetes & Digestive & Kidney Diseases, National Institutes of Health, Bethesda, MD 20892 USA. lujun@mail.nih.gov <lujun@mail.nih.gov>
Joseph C Lee
Marc L Salit
Margaret C Cam

Funding

Intramural NIH HHS
6 · The paper itself

Abstract

backgroundExtracting 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.

resultsUsing 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.

conclusionWe 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.

Indexed as

Databases, GeneticChromosome MappingDocumentationGene Expression ProfilingHumansOligonucleotide Array Sequence AnalysisOligonucleotide ProbesSensitivity and SpecificityTranscription FactorsOligonucleotide ProbesTranscription Factors

Identifiers

PMID17394657
PMCPMC1853115

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.