Figure 1. Demo result of GSEA analysis.
The map shows the ES value of GO obtained after GSEA analysis of the gene set. The curve in the upper part of the graph represents the dynamic ES value, and the highest point represents the ES value of this GO. The more significant the ES, the greater the impact on the gene set.
GSEA (Gene Set Enrichment Analysis) is a computational method used to determine whether a pre-defined gene set can show significant consistency differences in two biological states.
Pre-defined gene set: A gene set contains genes of interest, such as a certain pathway, a certain GO term, or hall marker gene set. Two biological states: the experimental group and the control group. It can be cancer and normal, male and female. Consistency differences: the genes in the pre-defined gene set show similar differences in two biological states; that is, the gene set in a certain pathway/GO entry is in the experimental group. It shows a consistent upward or downward trend with the control group.
In the method that is typically referred to as standard GSEA, there are three steps involved in the analytical process.The general steps are summarized below:
|Project name||GSEA analysis|
|Samples requirements||Our network analysis services in biology require you to provide specific requirements.|
|Detection cycle||Decide according to your needs.|
|Service including||We provide you with raw data and modeling results.|
Two groups of mRNA expression data (differential gene or gene of interest).
ComputaBio provides corresponding GSEA analysis as proven to be very useful for understanding the biochemical basis of physiological events at different stages of drug development (even in different fields such as materials science). ComputaBio team has been working in this field for more than ten years and has published his findings in top scientific journals. If you have a need for network analysis services, please feel free to contact us.