Super-delta: a new differential gene expression analysis procedure with robust data normalization.

ABSTRACT:

Background

Normalization is an important data preparation step in gene expression analyses, designed to remove various systematic noise. Sample variance is greatly reduced after normalization, hence the power of subsequent statistical analyses is likely to increase. On the other hand, variance reduction is made possible by borrowing information across all genes, including differentially expressed genes (DEGs) and outliers, which will inevitably introduce some bias. This bias typically inflates type I error; and can reduce statistical power in certain situations. In this study we propose a new differential expression analysis pipeline, dubbed as super-delta, that consists of a multivariate extension of the global normalization and a modified t-test. A robust procedure is designed to

SUBMITTER: Liu Y 

PROVIDER: S-EPMC5740711 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature