limma: Linear Models for Microarray Data

Gordon K. Smyth

Statistics for biology and health

December 29, 2005

10.1007/0-387-29362-0_23

Cited by 5,860

Abstract

Related Papers

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Yoav Benjamini, Yosef Hochberg|Journal of the Royal Statistical Society Series B (Statistical Methodology)|1995|108k

Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments

Gordon K. Smyth|Statistical Applications in Genetics and Molecular Biology|2004|12k

Variance stabilization applied to microarray data calibration and to the quantification of differential expression

Wolfgang Huber, Anja von Heydebreck, Holger Sültmann et al.|Bioinformatics|2002|2.6k

Identifying differentially expressed genes usingfalse discovery rate controlling procedures

Anat Reiner‐Benaim, Daniel Yekutieli, Yoav Benjamini|Bioinformatics|2003|1.8k

Use of within-array replicate spots for assessing differential expression in microarray experiments

Gordon K. Smyth, Jean Michaud, Hamish S. Scott|Computer applications in the biosciences|2005|1.4k