A statistical network pre-processing method to improve relevance and significance of gene lists in microarray gene expression studies.

ABSTRACT:

Background

Microarrays can perform large scale studies of differential expressed gene (DEGs) and even single nucleotide polymorphisms (SNPs), thereby screening thousands of genes for single experiment simultaneously. However, DEGs and SNPs are still just as enigmatic as the first sequence of the genome. Because they are independent from the affected biological context. Pathway enrichment analysis (PEA) can overcome this obstacle by linking both DEGs and SNPs to the affected biological pathways and consequently to the underlying biological functions and processes.

Results

To improve the enrichment analysis results, we present a new statistical network pre-processing method by mapping DEGs and SNPs on a biological network that can improve the relevance and significance of the

SUBMITTER: Agapito G 

PROVIDER: S-EPMC9516794 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature