HW4 - GSEA

Time estimated: 3 h; taken 5 h; date started: 2023-03-18; date completed: 2023-03-30

Procedure

1.1 Download required application and files

Gene Set Enrichment Analysis web tools have been used to perform GSEA preranked analysis. GSEA application was downloaded to local machine.

· Gene expression ranked set was selected and downloaded from GitHub (https://github.com/bcb420-2020/Student_Wiki/blob/e68e57b182c2cde6ad075b7da553ee37596f0ed3/MesenvsImmuno_RNASeq_ranks.rnk). File name: MesenvsImmuno_RNASeq_ranks.rnk.

· Gene sets was selected and downloaded from Baderlab (https://download.baderlab.org/EM_Genesets/current_release/Human/symbol/). File name: Human_GOBP_AllPathways_no_GO_iea_March_02_2023_symbol.gmt.

· Maximum gene set size was defined as 200.

· Minimum gene set size was defined as 15.

· Permutation was set to 1,000.

1.2 Perform GSEA analysis

· Run GSEA application

· Load files

· Run GSEAPreranked tool

· Set parameters

Results and interpretation

2.1. Explain the reasons for using each of the above parameters.

• Gene set size would determine the number of potential false positive (if too large) and false negative (if too small) results. Therefore, it was set as max: 200 and min: 15 by conventional.

• Gene set was selected from Baderlab, since it is regularly updated.

• Gene expression set was selected from a pre ranked dataset.

2.2 What is the top gene set returned for the Mesenchymal sub type?

2.2.1 How many genes in its leading edge?

147; including 83 core enrichment

2.2.2 What is the top gene associated with this geneset?

FBN1

2.3 What is the top gene set returned for the Immunoreactive subtype?

2.3.1 How many genes in its leading edge?

79; including 58 core enrichment

2.3.2 What is the top gene associated with this geneset?

PROCR

References:

Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005 Oct 25;102(43):15545-50. doi: 10.1073/pnas.0506580102. Epub 2005 Sep 30. PMID: 16199517; PMCID: PMC1239896.

Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, Puigserver P, Carlsson E, Ridderstråle M, Laurila E, Houstis N, Daly MJ, Patterson N, Mesirov JP, Golub TR, Tamayo P, Spiegelman B, Lander ES, Hirschhorn JN, Altshuler D, Groop LC. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet. 2003 Jul;34(3):267-73. doi: 10.1038/ng1180. PMID: 12808457.

Steipe, B. Modified: Isserlin, R. (2020-01-02) BCB420 - Computational System Biology. Retrieved 2023-01-20 from: BCB420 Winter 2023 course material