Decomposing the Apoptosis Pathway Into Biologically Interpretable Principal Components.

ABSTRACT: Principal component analysis (PCA) is one of the most common techniques in the analysis of biological data sets, but applying PCA raises 2 challenges. First, one must determine the number of significant principal components (PCs). Second, because each PC is a linear combination of genes, it rarely has a biological interpretation. Existing methods to determine the number of PCs are either subjective or computationally extensive. We review several methods and describe a new R package, PCDimension, that implements additional methods, the most important being an algorithm that extends and automates a graphical Bayesian method. Using simulations, we compared the methods. Our newly automated procedure is competitive with the best methods when considering both accuracy and speed and is the most a

SUBMITTER: Wang M 

PROVIDER: S-EPMC5987987 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature