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Hubbell, E. et al. (2002) Robust estimation for expression analysis. Bioinformatics, 18, 1585-1592 link


Irizarry, R. A. et al., (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics, 4, 249-264 link


A Model-Based Background Adjustment for Oligonucleotide Expression Arrays

Zhijin Wu , Rafael A. Irizarry , Robert Gentleman , Francisco Martinez-Murillo , Forrest Spencer

Journal of the American Statistical Association, 2004 vol 99 page 909 link


GCRMA2 is newer implementation of GCRMA which fixes a bug in original GCRMA implementation that introduces artifacts that can lead to the overestimation of pair wise correlation link

OMICSOFT Normalization of Microarray Data

Nearly all microarray expression data in OmicSoft Lands are re-processed from the signal intensity files in GEO/ArrayExpress, and normalized to improve cross-project comparisons. link

MA plot

The MA plot visualizes the relationship between measurement intensity in two samples. link

Moderated t-test (Limma Package in R)

The moderated t-test is used to rank genes in order of evidence for differential expression. They use an empirical Bayes method to shrink the probe-wise sample variances towards a common value and to augment the degrees of freedom for the individual variances (Smyth, 2004). The empirical Bayes moderated t-statistics test each individual contrast equal to zero. For each probe (row), the moderated F-statistic tests whether all the contrasts are zero. The F-statistic is an overall test computed from the set of t-statistics for that probe. This is exactly analogous to the relationship between t-tests and F-statistics in conventional anova, except that the residual mean squares and residual degrees of freedom have been moderated between probes. link