Visual Studio code



Download and extract a copy for Linux x64, e.g., for the latest version 1.58.0,

cd ${HPC_WORK}
tar xvfz code-stable-x64-1625728370.tar.gz
ln -sf ${HPC_WORK}/VSCode-linux-x64/bin/code ${HPC_WORK}/bin/code

By default it requires chrome-sandbox is owned by root and has mode 4755 which could be achieved at CSD3 by

sudo chown root:root chrome-sandbox
sudo chmod 4755 chrome-sandbox

Unfortunately, as ordinary users this is impossible and we use without this option.


Start for reasons above,

code --no-sandbox

ceuadmin module

This is called with

module load ceuadmin/VSCode/1.76.2

which enables executation with relevant command-line arguments.

Jupyter notebook

We could start our virtual environment as described in hail, e.g.,

cd ~/rds/results/public/gwas/ukb_exomes/tutorials
code --no-sandbox 01-genome-wide-association-study.ipynb &

which greatly simplifies the procedure as described for genebass. MAKE sure various extensions/options suggesed from the session.

Markdown document

It will be displayed by design.


From Visual Studio Code, install CodeGPT.

Supply an API key from Open AI,, entered via Ctrl-Shift-p for CodeGPT: Set API Key.

Create a file such as testCodeGPT.R with comments # I would like to draw a forest plot and key in Ctrl-Shift-i.

Here is an example,

# Can I draw a Manhattan plot of GWAS

with answer below,

Yes, you can draw a Manhattan plot of GWAS in R using the qqman package.

Here's a sample code:

# install and load the `qqman` package

# read in the GWAS results file
gwas_results <- read.table("my_gwas_results.txt", header=T)

# specify the chromosome column
chr_col <- "CHR"

# specify the p-value column
pval_col <- "P_VALUE"

# draw the Manhattan plot
manhattan(gwas_results, chr=chr_col, p=pval_col)

Replace "my_gwas_results.txt" with the actual name of your GWAS results file. Also, make sure to specify the correct column names for chromosome and p-value in chr_col and pval_col, respectively.