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Aim:
Identify statistically significant (FDR < 0.05) differentially expressed genes. Visualise results with PCA plots, heatmaps and volcano plots.
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Use QUTs rVDI virtual desktop machines
Install R and RStudio on your own PC
Use the provided PCs in the QUT computer labs
Option1: Use QUTs rVDI virtual desktop machines
This is the preferred method, as R and RStudio is already installed, as are all the required R packages needed for analysis. Installing all of these can take over 30 minutes on your own PC, so using an rVDI machine saves time.
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Log on with your QUT username and password
Option2: Install R and RStudio on your own PC
Go to the following page https://posit.co/download/rstudio-desktop/ and follow instructions provided to install first R and then Rstudio.
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https://posit.co/download/rstudio-desktop/
Option3: Use the provided PCs in the QUT computer labs
The PCs in the computer labs already have R and RStudio installed. If using this option, you will need to install the required R packages (unlike rVDI). The code for installing these packages is in the analysis section below.
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To access this count table:
Go to the/sandpit/demo/run3_full_pipeline/ folder that contains the results from running the nfcore/rnaseq pipeline. The output folders from task 3 look like this:
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Now let’s find the full path to the ‘salmon.merged.gene_counts.tsv’ file:
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