Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects.

By George C. Tseng, M. Oh, L. Rohlin, James C. Liao, Wing Hung Wong. Nucleic Acids Research, 2001

641 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/aa21536103308d8c46c4ab67473f2448bc8bd1f6

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Citations in the corpus

Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. (2002, background): “In practice, a maximal invariant set tends to be too small and an iterative procedure for finding an approximately invariant set of genes has been proposed (19,20).”
Design issues for cDNA microarray experiments (2002, background): “2 ), in which each hybridization is done twice, with the dye assignments reversed in the second hybridization, are useful for reducing systematic bia”
Use of within-array replicate spots for assessing differential expression in microarray experiments (2005, background): “Repeatability of the logratios across replicate spots within arrays can be used as a basis for removing outlier spots (Tseng et al., 2001; Hoffmann et al., 2002; Yang et al., 2002; Jenssen et al., 2002; Lyne et al., 2003; König et al., 2004), to construct spot-quality measures (Beissbarth et al.”
ChIP-chip: considerations for the design, analysis, and application of genome-wide chromatin immunoprecipitation experiments. (2004, methodology): “Even advanced techniques that select rank-invariant elements to use for normalization fail on highly skewed data [51].”
The Acetate Switch (2005, background): “In contrast, these cells down-regulate the transcripts and proteins of the PTAACKA pathway, nonacetate carbon transport systems, and glycolytic enzymes (226, 328, 329, 342, 451).”
Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis (2007, background): “for systematic expression variation due to well-characterized laboratory and technical sources [12,13,20].”
Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain (2010, methodology): “rank invariant normalization method [29–31] and then log2 transformed for mRNA analysis.”
Microarray data normalization and transformation (2002, neutral): “ln(2) and ∂ ∂x 1 x [ln(x)]= , = log2 (Ai)–log2(Bi).”