Background: Normalization is an important step for microarray data analysis to minimize biological and technical variations. Choosing a suitable approach can be critical. The defa...
Background: Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for ...
Timothy Lu, Christine M. Costello, Peter J. P. Cro...
Background: High-throughput sequencing technologies, such as the Illumina Genome Analyzer, are powerful new tools for investigating a wide range of biological and medical question...
James H. Bullard, Elizabeth Purdom, Kasper D. Hans...
Background: Normalization is essential in dual-labelled microarray data analysis to remove nonbiological variations and systematic biases. Many normalization methods have been use...
Huiling Xiong, Dapeng Zhang, Christopher J. Martyn...
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...