Research Paper Volume 13, Issue 19 pp 23245—23261

Identification of potential target genes of non-small cell lung cancer in response to resveratrol treatment by bioinformatics analysis


Figure 7. GSCA online database was selected to analyze the single nucleotide variation, methylation and pathway activity of validated genes. (A) Waterfall plots, gives a single nucleotide variation of in LUAD and LUSC gene sets. (B) Methylation of hub genes, Blue points represented a methylation upregulation in tumors, red points represented a methylation downregulation in tumors, the deeper of color, the higher the difference. Student T test were performed to define the methylation difference between tumor and normal samples. The association between mRNA expression and methylation was based on Person’s product moment correlation coefficient, and followed a t distribution. Blue points represented negative correlation, and red represented positive correlation, the deeper of color, the higher the correlation. P value was adjusted by false discovery rate (FDR), FDR ≤ 0.05 was considered as significant. Size of the point represents statistic significance (C) Effects of validated gene on cell pathway activity, gene expression was divided into 2 groups (High and Low) by median expression, the difference of pathway activity score (PAS) between groups was defined by student T test, P value was adjusted by FDR, FDR ≤ 0.05 was considered as significant. Pathway Activity module presents the correlation of genes expression with pathway activity groups (activation and inhibition) that defined by pathway scores.