Functional Analysis- Kevin Lin

Presentation (PowerPoint)
https://docs.google.com/presentation/d/1o2h4TKz6GRFNZQe6_GCbIJ3TLyGuuG88nOtaQT7Qf6w/edit?usp=sharing

Challenges Faced:

  • Once again, the issue of knowing where to begin was a very time consuming problem. I struggled with creating gene vectors of up and down regulated DEGs. However, this was overcome by substituting the vector with a column of a created matrix. The gene vectors were eventually generated after consulting my team technical lead.

  • The answer to the previous challenge led to an error when it came to running the GSEA function with the matrix column. By contacting a technical lead, I substituted the column of the created matrix with an actual gene vector and by adjusting p value cutoffs, enriched terms were identified. This allowed for the gseaplot2 to run and create a graph with visible peaks.

Summary of Work:

  • Defined significant DEGs into a vector and converted gene symbols to their entrez IDs using the org.Hs.eg.db database

  • Visualized DEGs after enrichGO analysis using barplots

  • Visualized DEGs after enrichKEGG pathway analysis using dot plots

  • Observed complex associations between genes using gene-concept networks

  • Conducted global gene set enrichment analysis using hallmark gene sets

Further Notes:

  • Although my graphs were generated, I continue to think I could have done a better job with this section of the project. My refined data had very little enriched terms even though my graphs were said to look correct. Of course, even with a handful of enriched terms, I was able to draw conclusions regarding the differences in gene expression between colorectal cancer cells and normal cells.