Claire Simpson - Cell Signaling Technology Neo4j Health Care & Life Sciences Workshop 2021

1. November 9, 2021
Analyzing Perturbed Co-Expression
Networks in Cancer Using a Graph
Database
Claire Simpson

2. 2
TCGA input data
Building the coexpression network
Pagerank
Louvain clustering
Shortest paths
Conclusion
Overview

3. The Cancer Genome Atlas input data
PRAD, LUAD, LUSC, BRCA, KIRC, THCA RNA-seq data (tumor and matched
normal tissue)
3

4. Building the network
4
Adjacent normal tissue Tumor tissue

5. Building the network
5

6. Overview of networks
6

7. Overview of networks
7

8. Pagerank
8

9. Pagerank
9

10. Pagerank
10

11. Pagerank scores between cancer types
11
Correlation between PR scores for each gene between pairs of tissue types (e.g.
lung and kidney)

12. Louvain clustering and gene ontology analysis
12

13. Louvain clustering and gene ontology analysis
13

14. Louvain clustering
14

15. Change in degree between communities
15
DNA
replication
Immune response

16. Shortest paths
16

17. Shortest paths
17

18. Conclusion and further questions
▪ Adjacent normal tissue vs normal tissue, RNA vs protein
▪ How does coexpression matrix correlate with known interactions?
▪ Analyzing these networks using Neo4j was extremely fast and technically
straightforward
18

19. Rooted in Science. Grounded in Reproducibility.SM
19
Thank you to Florian Gnad for advising!