Comparison of merging and meta-analysis as alternative approaches for integrative gene expression analysis.

ABSTRACT: An increasing amount of microarray gene expression data sets is available through public repositories. Their huge potential in making new findings is yet to be unlocked by making them available for large-scale analysis. In order to do so it is essential that independent studies designed for similar biological problems can be integrated, so that new insights can be obtained. These insights would remain undiscovered when analyzing the individual data sets because it is well known that the small number of biological samples used per experiment is a bottleneck in genomic analysis. By increasing the number of samples the statistical power is increased and more general and reliable conclusions can be drawn. In this work, two different approaches for conducting large-scale analysis of microarray

SUBMITTER: Taminau J 

PROVIDER: S-EPMC4393058 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature