Covid-19 Lockdown Learning

Since the beginning of the Covid-19 lockdown, I’ve been live-streaming a bioinformatics tutorial a day on YouTube. The video above is the first lesson, taking beginners through installing a Virtual Machine that we will use for subsequent sessions.

I’ve been amazed by the reception these cobbled-together videos have received. I’ve been learning about live-streaming and managing a YouTube channel on the fly, while also trying to come up with a coherent lesson every day, continue to make progress in my actual job, home school the kids and enable my wife to continue to make progress with her own job (just as she enables me – we make a good team).

As I write, I’ve made 36 of these ~1hr videos, and we’ve got through the basics of the command line, downloading RNA-Seq data from the SRA, QC with FastQC and MultiQC and quantification using Salmon and then analysing that data using DESeq2. In the 36th session, I covered making a heatmap from the expression data of the differentially expressed genes.

We’ve been analysing samples from the GEO dataset GSE147507 – which has mock and SARS-CoV-2 infected lung cell lines. I wanted the analysis I used for demonstration to be relevant to the current situation.

If you’re interested in learning a bit of bioinformatics, and how the SARS-CoV-2 virus effects gene expression in lung cells in culture, you can find the playlist of all of my “Lockdown Learning” bioinformatics lessons here:

https://www.youtube.com/playlist?list=PLzfP3sCXUnxEu5S9oXni1zmc1sjYmT1L9

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