Progress Summary - Functional Analysis - Daniel Drucker
Contribution: Processing data through the enrichment analysis, gene concept network, and the transcriptional factor analysis
- Coming from a completely minimal biology background, I had a difficult time understanding what exactly the outputs mean. My group-mate, who is much more well-versed in biology, was helpful in identifying the meanings of the cellular functions affected that are output by the enrichment analysis.
- I also had a hard time understanding what the gene concept network plots and STRING database output elucidate in associating certain genes with one another.
- Still more trouble being familiar with the semantics of R syntax, which made the transcriptional factor analysis onerous, but not impossible through some trial and error.
Summary of Work
- Using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis to associate differential expressions with actual cellular functions through using enrichGO(), enrichKEGG(), and outputting plots of the results.
- Produced a gene concept network plot using enrichDGN() and cnetplot().
- Used STRING database to produce a visual to forge associations between gene functions.
- Transcriptional factor analysis using data from MSig database and gene set enrichment analysis, producing another network plot to visualize gene associations.
- This is the step that intrigued me most because it produces a physical, biological meaning in telling us what cellular functions are affected according to our data. I regret that I lacked the biological knowledge to appreciate the details of those meanings.