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Table 4 Level of granularity of number of DEGs in different steps of analysis. Each row represents a step of analysis. The second from the last row represents the number of biomarker genes discovered from non-treatment and treatment studies. The last row shows the number of biomarker genes that could be used to design a lab experiment for further exploration of dynamics in lung cancer development

From: Computational identification of biomarker genes for lung cancer considering treatment and non-treatment studies

Tools/Analysis

Number of DEGs

 

Non-Treatment

Treatment

GEO Built-in Filter

16,876

GEO2R

407

547

ReactomeFI

166

260

Cytohubba

38

51

Hub genes (Common in two algorithms)

21

24

MCODE (Genes present in clusters)

63

55

Biomarkers (Common in Hub and MCODE)

16

16

Survival Analysis

14

14