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There are a number of accepted normalization techniques that can be applied to microarray data, with varying levels of complexity and transparency.
To identify unknown lncRNAs by RIP, the co-immunoprecipitated RNA pool can be applied to microarray analyses or RNA-seq, as described later [ 19, 23, 28].
Although the current statistic was developed for analyzing HiCEP data, it can also be applied to microarray data since the input data (expression matrix) is the same.
We also allow the user to specify a custom background list, allowing our tool to be applied to microarray data and other data not generated from genome- or transcriptome-wide assays.
Bayesian analysis can also be applied to microarray data [ 13, 20, 21], and may be useful in this context to draw more information out of the distribution of intensities and ratios in the data.
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In this study, chemometric strategies were applied to microarray data in order to develop an appropriate normalisation method.
This concept has been applied to microarray transcriptome data [3] and proteome data [4].
Cy3- or Cy5-labeled probe mixtures were applied to microarray slides, which were then incubated for 16 h at 55°C in a MAUI hybridization chamber.
Biclustering has successfully been applied to microarray gene expression data from various systems to uncover abnormally expressed functional modules [36], [37].
Briefly, fragmented genomic template DNA was denatured, mixed with Thermo Sequenase DNA Polymerase USB Corporationn) and fluorescently labeled dideoxynucleotides before being applied to microarray slides for a 20 minute isothermic APEX reaction.
Both methods have been applied to microarray analysis as well.
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