ArticleBMC genomics2009
Evaluating annotations of an Agilent expression chip suggests that many features cannot be interpreted.
Article in BMC genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The trial behind it
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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Who cites it
6 citing papers in PubMed.
- The transcriptional profiling of human in vivo-generated plasma cells identifies selective imbalances in monoclonal gammopathies.PloS one · 2017Article
- Article
- Genome-wide expression and copy number analysis identifies driver genes in gingivobuccal cancers.Genes, chromosomes & cancer · 2012Article
- Potential role of a navigator gene NAV3 in colorectal cancer.British journal of cancer · 2012Article
- Systems-wide RNAi analysis of CASP8AP2/FLASH shows transcriptional deregulation of the replication-dependent histone genes and extensive effects on the transcriptome of colorectal cancer cells.Molecular cancer · 2012Article
- Maize microarray annotation database.Plant methods · 2011Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundWhile attempting to reanalyze published data from Agilent 4 x 44 human expression chips, we found that some of the 60-mer olignucleotide features could not be interpreted as representing single human genes. For example, some of the oligonucleotides align with the transcripts of more than one gene. We decided to check the annotations for all autosomes and the X chromosome systematically using bioinformatics methods.
resultsOut of 42683 reporters, we found that 25505 (60%) passed all our tests and are considered "fully valid". 9964 (23%) reporters did not have a meaningful identifier, mapped to the wrong chromosome, or did not pass basic alignment tests preventing us from correlating the expression values of these reporters with a unique annotated human gene. The remaining 7214 (17%) reporters could be associated with either a unique gene or a unique intergenic location, but could not be mapped to a transcript in RefSeq. The 7214 reporters are further partitioned into three different levels of validity.
conclusionExpression array studies should evaluate the annotations of reporters and remove those reporters that have suspect annotations. This evaluation can be done systematically and semi-automatically, but one must recognize that data sources are frequently updated leading to slightly changing validation results over time.
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Registered trials
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