PcaGoPromoter - An R package for functional interpretation of principal component analysis of genome-wide gene expression data

ABSTRACT: Background and aim: Analysis of data obtained from genome wide gene expression experiments is challenging, due to the huge amount of variables, management of the data and the need for multivariate analysis. We here present the R package: pcaGoPromoter that facilitates the interpretation of genome wide expression data to overcome these problems. In a first step principal component analysis is applied to overview any differences between the observations and possible groupings. The next step is interpretation of the principal components with respect to both biological function and involvement of predicted transcription factor binding sites. The robustness of the results is evaluated using cross validation. Illustrative plots of PCA score plots and Gene Ontology terms are available. To illustr

ORGANISM(S): Homo sapiens

SUBMITTER: Morten Hansen 

PROVIDER: E-GEOD-27071 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress