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
start Rstudio (if you installed workflowr, you can just open the QGT-Columbia-HKI.Rproj)
#R setup
Code
#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")## make sure these are installed# library(data.table)# library(BEDMatrix)# library(Rfast)# library(susieR)# library(coloc)#installing base minicondainstall.packages("keras")reticulate::install_miniconda("miniconda")
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.
---title: "Lab Setup"output: html_documentdate: '2022-05-06'---copied from QGT 2023 posit## 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](https://github.com/hakyimlab/MetaXcan/blob/master/README.md#example-conda-environment-setup), which will install all the python modules needed for this analysis session- [ ] download data and software [from Box](https://uchicago.box.com/s/zhapf2zfxcpj7thvq4sjnqale3emleum). This will have copies of all the software repositories and the models- [ ] download software - download metaxcan repo - download torus repo- [ ] download prediction models from predictdb.org - [ ] install R/RStudio/tidyverse package- [ ] 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```{r eval=FALSE}#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")## make sure these are installed# library(data.table)# library(BEDMatrix)# library(Rfast)# library(susieR)# library(coloc)#installing base minicondainstall.packages("keras")reticulate::install_miniconda("miniconda")```#Setting up Conda Environment```{bash, eval=FALSE}#adding pathexportPATH=$PATH:/cloud/project/miniconda/bin# adding repos/datagit clone https://github.com/hakyimlab/QGT-Columbia-HKI-repo.gitgit clone https://github.com/hakyimlab/MetaXcan.gitconda config --append channels conda-forgeconda config --append channels biocondaconda env create -f /cloud/project/MetaXcan/software/conda_env.yamlconda activate imlabtools```Set the Ram to 5gb in order to create the environment. #Box DataTo 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.