DGE Analysis - Croix Mikofsky

Progress Summary- DGE Analysis

Group presentation:
https://docs.google.com/presentation/d/1oHrdFy0xB7RqUCjVHbcnGOkWD54uY-TRsthBLQ1j1NA/edit?usp=sharing

Challenges faced:
I had a problem with my model matrix. Also I discovered an early error with the ordering of my affyBatch object which contributed to the strange looking PCA plots. Also a problem w/ our PCA and outliers.
All of these were solved through group or independent troubleshooting.

(note: as for the identification of outliers, I have yet to figure out a concrete method for this-- even after the final. I tried to do it using my PCA data but maybe that was misguided).

Summary of work:
Technical - Using R tools to conduct a differential gene expression analysis
filtered, annotated gene set, produced a heatmap and volcano plot
Tools - RStudio, Troubleshooting (stackoverflow, R website, etc), slack, google meet, stem away forum
Soft Skills - Cultural competency

Further notes:
Looking back, I was quite unsure throughout whether or not I had done the steps correctly. After finishing and looking up my most differentially expressed genes, it was a relief when I found that some of them were actually biologically relevant to colorectal cancer.

All the statistical operations we have done to both prepare and analyze the data make me want to go learn just how exactly those functions work, (ex. rma(), topTable(), collapseRows(), etc.)

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