Bioinformatics analysis of Affymetrix microarray gene expression data, comparing leukocytes with the gain-of-function genotype to those with a non-variant genotype.

<p>Principal Component Analysis (PCA) scatter plot using Partek analysis is shown in the upper left corner. PCA is mathematically defined as an orthogonal linear transformation that transforms the data to a new coordinate system such that the greatest variance by any projection of the data comes to lie on the first coordinate (called the first principal component), the second greatest variance on the second coordinate, and so on. Each dot represents a patient's expression profile; the blue color dots represent gain-of-function and red show non-variant genotypes. Analysis using the Ingenuity Pathway Tools (IPA) software utilizes a repository of biological interactions and functional annotations created from millions of individually modeled relationships. The genes in red indicate increased expression and blue represents decreased expression, comparing gain-of-function with non-variant individuals. Primary networks identified were ERK1/2, p38MAPK, and NFκB networks.