A two-way rectification method for identifying differentially expressed genes by maximizing the co-function relationship.

ABSTRACT:

Background

The identification of differentially expressed genes (DEGs) is an important task in many biological studies. The currently widely used methods often calculate a score for each gene by estimating the significance level in terms of the differential expression. However, biological experiments often have only three duplications, plus plenty of noises contain in gene expression datasets, which brings a great challenge to statistical analysis methods. Moreover, the abundance of gene expression levels are not evenly distributed. Thus, those low expressed genes are more easily to be detected by fold-change based methods, which may results in high false positives among the DEG list. Since phenotypical changes result from DEGs should be strongly related to several distinct cellula

SUBMITTER: Chen B 

PROVIDER: S-EPMC8229713 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature