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BMCBI
2005

Quality determination and the repair of poor quality spots in array experiments

10 years 1 months ago
Quality determination and the repair of poor quality spots in array experiments
Background: A common feature of microarray experiments is the occurence of missing gene expression data. These missing values occur for a variety of reasons, in particular, because of the filtering of poor quality spots and the removal of undefined values when a logarithmic transformation is applied to negative background-corrected intensities. The efficiency and power of an analysis performed can be substantially reduced by having an incomplete matrix of gene intensities. Additionally, most statistical methods require a complete intensity matrix. Furthermore, biases may be introduced into analyses through missing information on some genes. Thus methods for appropriately replacing (imputing) missing data and/or weighting poor quality spots are required. Results: We present a likelihood-based method for imputing missing data or weighting poor quality spots that requires a number of biological or technical replicates. This likelihood-based approach assumes that the data for a given spot...
Brian D. M. Tom, Walter R. Gilks, Elizabeth T. Bro
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2005
Where BMCBI
Authors Brian D. M. Tom, Walter R. Gilks, Elizabeth T. Brooke-Powell, James W. Ajioka
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