Week 4- DESeq2

Arnab M -

Hi guys, It’s Arnab and this is my fourth weekly update on my senior research project: Exploring the Genomic Effects of PNPLA7 Mutations on Cerebral Palsy through RNA Sequencing.

I was ecstatic to re-transition back to the lab, jumping right into all my last week’s assigned readings surrounding DESeq2. We tested my knowledge by tackling a DESeq2 Vignette (also known as a tutorial) from Bioconductor. Bioconductor is a major open-source bioinformatics software that DESeq2 heavily utilizes and will serve as our pathway to downloading and installing all the necessary tools for this step. Additionally, this is when we get to start using R Studio and its user-friendly commands and processes as opposed to my previous work with the Linux terminal and shell script.

I started off by viewing the Vignette’s instructions on how to organize our example HTSeq data files (called pasilla) into a data frame, with accurately labeled rows and columns. This required multiple lines of code, thankfully R Studio allows you to code in the terminal while maintaining your code script all on the same page. This made my life so much easier when writing the Vignette’s code (as seen in my attached image on the top left) and eventually, when the data was coherently organized we could use certain command functions to graph them (as seen in my attached image on the bottom right).

All of these rigorous and complicated practices with the Pasilla Vignette serve to aid in my actual handling of the data when I run DESeq2 later on. As for now, I am still running my code in htseq so I can start the process of DESeq 2 later this week.

Although this last week has been a reading and coding nightmare, I am glad I can understand and employ these valuable skills I am learning from Dr. Kruer’s Lab. Can’t wait to see you next week!

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    Hi Arnab! Great work. I'm interested in how these skills in coding, and working with R Suite and Linux, may be useful in other applications in your future education and career path. It sounds like you are gaining some exceptional experience!
    Hey Arnab! Could you go into more clarity about the coding part of your project? It seems very cool!
    Hi! I would love to clarify the coding aspect of my project. So basically in this stage of the project we are using R Studio to accomplish our data analysis. Coding is extremely powerful and especially with R's user-friendliness it is easily accessible to writing code, testing code, and visualizing data, all in the same window. With just a single line of code, I can create directory pathways, activate tools from specific DESeq2 packages, and create GGplot graphs (bioinformatics graphs) as depicted in the attached image. I hope this grants you more insight into the intricacies and beauty that is the field of bioinformatics and data analysis!

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