Meta-analysis based gene expression profiling reveals functional genes in ovarian cancer.

ABSTRACT:

Background

Ovarian cancer causes high mortality rate worldwide, and despite numerous attempts, the outcome for patients with ovarian cancer are still not well improved. Microarray-based gene expressional analysis provides with valuable information for discriminating functional genes in ovarian cancer development and progression. However, due to the differences in experimental design, the results varied significantly across individual datasets.

Methods

In the present study, the data of gene expression in ovarian cancer were downloaded from Gene Expression Omnibus (GEO) and 16 studies were included. A meta-analysis based gene expression analysis was performed to identify differentially expressed genes (DEGs). The most differentially expressed genes in our meta-analysis were se

SUBMITTER: Zhao L 

PROVIDER: S-EPMC7677829 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature