{ "_id": "6a1974b3acfb0bcc41df0680", "Package": "vsn", "Version": "3.80.0", "Title": "Variance stabilization and calibration for microarray data", "Authors@R": "c(\nperson(\"Wolfgang\", \"Huber\", email=\"wolfgang.huber@embl.org\", role = c(\"aut\",\"cre\")),\nperson(\"Anja\", \"von Heydebreck\", role = c(\"aut\")),\nperson(\"Dennis\", \"Kostka\", role = c(\"ctb\")),\nperson(\"David\", \"Kreil\", role = c(\"ctb\")),\nperson(\"Hans-Ulrich\", \"Klein\", role = c(\"ctb\")),\nperson(\"Robert\", \"Gentleman\", role = c(\"ctb\")),\nperson(\"Deepayan\", \"Sarkar\", role = c(\"ctb\")),\nperson(\"Gordon\", \"Smyth\", role = c(\"ctb\")),\nperson(\"Federal Ministry of Research, Technology and Space of Germany, DHGP\", role=\"fnd\"))", "Maintainer": "Wolfgang Huber ", "Description": "The package implements a method for normalising microarray\nintensities from single- and multiple-color arrays. It can also\nbe used for data from other technologies, as long as they have\nsimilar format. The method uses a robust variant of the\nmaximum-likelihood estimator for an additive-multiplicative\nerror model and affine calibration. The model incorporates data\ncalibration step (a.k.a. normalization), a model for the\ndependence of the variance on the mean intensity and a variance\nstabilizing data transformation. Differences between\ntransformed intensities are analogous to \"normalized\nlog-ratios\". However, in contrast to the latter, their variance\nis independent of the mean, and they are usually more sensitive\nand specific in detecting differential transcription.", "Reference": "[1] Variance stabilization applied to microarray data\ncalibration and to the quantification of differential\nexpression, Wolfgang Huber, Anja von Heydebreck, Holger\nSueltmann, Annemarie Poustka, Martin Vingron; Bioinformatics\n(2002) 18 Suppl1 S96-S104. 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