ArticleBMC bioinformatics2005
MASQOT: a method for cDNA microarray spot quality control.
Article in BMC bioinformatics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- MOF: an R function to detect outlier microarray.Genomics, proteomics & bioinformatics · 2008Article
- Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data.BMC genomics · 2008Article
- Optimization of cDNA microarrays procedures using criteria that do not rely on external standards.BMC genomics · 2007Article
- Improving missing value imputation of microarray data by using spot quality weights.BMC bioinformatics · 2006Article
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Authors and funding
7 authors.
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Abstract
backgroundcDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more.
resultsA novel methodology for cDNA microarray spot quality control is outlined. Multivariate discriminant analysis was used to assess spot quality based on existing and novel descriptors. The presented methodology displays high reproducibility and was found superior in identifying unreliable data compared to other evaluated methodologies.
conclusionThe proposed methodology for cDNA microarray spot quality control generates non-discrete values of spot quality which can be utilized as weights in subsequent analysis procedures as well as to discard spots of undesired quality using the suggested threshold values. The MASQOT approach provides a consistent assessment of spot quality and can be considered an alternative to the labor-intensive manual quality assessment process.
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