R we really coding in lab instead of pipetting??

I’m not going to lie; I really dislike anything that has to do with coding. It is just so stressful to never know whether or not your code is going to work and when it doesn’t work, which is 99.9% of the time, debugging is the worst. So, when I realized we were going to have to code in R in order to make our data from the qPCR meaningful, I was pretty scared. 

 At first, I was right to be scared. For the first R exercise, I had no idea what was going on even after rereading and rereading the instructions provided. Thankfully, Leslie and Catherine were really patient and answered all my questions even when I was so confused that I didn’t even know what question to ask. I think it was also super helpful that for all of the exercises, we were only ever running a few lines of code for each step. Slowly, the code started to make more sense. My heat maps and dendrograms started working and once I was finally able to get my code working for the gene ontology part, it was so interesting to see the results that came up for gene function of upregulated and downregulated genes from etoposide treatment. 

 Although I’m still trying to wrap my head around PCA plots, ultimately, performing the RNA-seq data analysis helped me to appreciate the use of coding in the context of BE. There is so much useful information that can come out of what begins as an insanely large and isoteric dataset when you make sense of it using R. Who knows, maybe I’ll even suggest using RNA-seq to my UROP supervisor for my current UROP project.

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