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- Bylesjö, Max, et al.
(författare)
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MASQOT : a method for cDNA microarray spot quality control.
- 2005
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 6, s. 250-
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Tidskriftsartikel (refereegranskat)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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| 2. |
- Bylesjö, Max, et al.
(författare)
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MASQOT-GUI : spot quality assessment for the two-channel microarray platform
- 2006
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 22:20, s. 2554-2555
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Tidskriftsartikel (refereegranskat)abstract
- MASQOT-GUI provides an open-source, platform-independent software pipeline for two-channel microarray spot quality control. This includes gridding, segmentation, quantification, quality assessment and data visualization. It hosts a set of independent applications, with interactions between the tools as well as import and export support for external software. The implementation of automated multivariate quality control assessment, which is a unique feature of MASQOT-GUI, is based on the previously documented and evaluated MASQOT methodology. Further abilities of the application are outlined and illustrated. AVAILABILITY: MASQOT-GUI is Java-based and licensed under the GNU LGPL. Source code and installation files are available for download at http://masqot-gui.sourceforge.net/
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| 3. |
- Bylesjö, Max, et al.
(författare)
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Orthogonal projections to latent structures as a strategy for microarray data normalization
- 2007
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 8:207
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundDuring generation of microarray data, various forms of systematic biases are frequently introduced which limits accuracy and precision of the results. In order to properly estimate biological effects, these biases must be identified and discarded.ResultsWe introduce a normalization strategy for multi-channel microarray data based on orthogonal projections to latent structures (OPLS); a multivariate regression method. The effect of applying the normalization methodology on single-channel Affymetrix data as well as dual-channel cDNA data is illustrated. We provide a parallel comparison to a wide range of commonly employed normalization methods with diverse properties and strengths based on sensitivity and specificity from external (spike-in) controls. On the illustrated data sets, the OPLS normalization strategy exhibits leading average true negative and true positive rates in comparison to other evaluated methods.ConclusionsThe OPLS methodology identifies joint variation within biological samples to enable the removal of sources of variation that are non-correlated (orthogonal) to the within-sample variation. This ensures that structured variation related to the underlying biological samples is separated from the remaining, bias-related sources of systematic variation. As a consequence, the methodology does not require any explicit knowledge regarding the presence or characteristics of certain biases. Furthermore, there is no underlying assumption that the majority of elements should be non-differentially expressed, making it applicable to specialized boutique arrays.
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