Capturing heterogeneity in gene expression studies by surrogate variable analysis.
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...Removing batch effects and using surrogate variables in differential expression analysis have been shown to reduce dependence, stabilize error rate estimates, and improve reproducibility (see [2, 3, 4] for more detailed information)....
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Cites methods from "Capturing heterogeneity in gene exp..."
...ordinary least squares, linear mixed effects models [16], limma [17], or surrogate variable analysis [18,19], to obtain estimates B̂0 and B̂1....
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"Capturing heterogeneity in gene exp..." refers methods in this paper
...To demonstrate these issues, we considered two straightforward significance analysis applications of the well-established singular value decomposition approach previously utilized in genomics [40,41]....
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...[41] also performed this singular value decomposition of whole-genome SNP genotypes (coded as 0, 1, or 2) in order to account for systematic sources of variation due to population substructure....
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"Capturing heterogeneity in gene exp..." refers background in this paper
...The overall goal of SVA is to provide a more accurate and reproducible parsing of signal and noise in the analysis of an expression study when EH is present. One way in which signal is commonly quantified is through a significance analysis [...
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