The method of unstandardized data Distribution in Illumina microarray

This article mainly introduces the Illumina microarray non-standardized data distribution method related knowledge, the content is detailed and easy to understand, the operation is simple and fast, has a certain reference value, I believe that everyone after reading this Illumina microarray unstandardized data distribution method article will have a harvest, let's take a look at it.

Unlike the drawing of affymetrix chip data distribution based on affy package, Illumina microarray data distribution is based on lumi package:

Boxplot-method

Density-method (or hist)

The affy package can also take advantage of boxplot, but the density map uses hist, so here are some lumi packages for the Illumina microarray drawing process (GSE63229):

Obtain LumiBatch objects based on lumiR.batch, and draw directly based on the objects:

> n.sample = length (LumiBatch$sampleID) > cols=rainbow (n.sample) > par (cex = 0.7) > if (n.sample > 40) par (cex = 0.5) > boxplot (LumiBatch,col = cols, las = 2)

The density map is (same as hist):

> par (cex = 0. 7) > if (n.sample > 40) par (cex = 0. 5) > density (LumiBatch,col = cols, las = 2) this article on "methods of unstandardized data distribution in Illumina microarray" ends here. Thank you for reading! I believe you all have a certain understanding of the knowledge of "Illumina microarray unstandardized data distribution method". If you want to learn more knowledge, you are welcome to follow the industry information channel.