Setting up your own system

Linux is the operating system of choice to run bioinformatics software. You will need either a computer running linux or or mac os, which has a linux-like environment.

• install anaconda/miniconda
• define imlabtools conda environment how to here, which will install all the python modules needed for this analysis session
• download data and software from Box. This will have copies of all the software repositories and the models
• download software
  • download metaxcan repo
• download prediction models from predictdb.org
• install R/RStudio/tidyverse package
• install R packages
• git clone https://github.com/hakyimlab/QGT-Columbia-HKI.git
• start Rstudio (if you installed workflowr, you can just open the QGT-Columbia-HKI.Rproj)

R setup

#install R packages 
install.packages("remotes")
library(remotes)
remotes::install_github("stephenslab/susieR") #gives the most up to date SusieR 
install.packages("coloc")
install.packages("tidyverse")
install.packages("R.utils")
install.packages("remotes")
remotes::install_github("simingz/ctwas", ref = "develop")


#cTWAS install
install.packages("R.utils")
install.packages("remotes")
remotes::install_github("simingz/ctwas", ref = "develop")
library(ctwas)


## make sure these are installed
# library(data.table)
# library(BEDMatrix)
# library(Rfast)
# library(susieR)
# library(coloc)

#installing base miniconda
install.packages("keras")
reticulate::install_miniconda("miniconda")

Setting up Conda Environment

#adding path
export PATH=$PATH:/cloud/project/miniconda/bin
# adding repos/data
git clone https://github.com/hakyimlab/QGT-Columbia-HKI-repo.git
git clone https://github.com/hakyimlab/MetaXcan.git
conda config --append channels conda-forge
conda config --append channels bioconda
conda env create -f /cloud/project/MetaXcan/software/conda_env.yaml
conda activate imlabtools

Set the Ram to 5gb in order to create the environment.

Box Data

To upload the data. I first downloaded the box folder onto a local machine and then compressed the folders in the box folder to upload onto the server.

Notes: For some reason setting up the environment and uploading the data will continue to use a lot of background RAM set sure to close the project and reopen to close extraneous programs.