added plink 1.90 beta module

plink/1.90b/.gitignore

@@ -0,0 +1 @@
+plink

plink/1.90b/README.md

@@ -0,0 +1,43 @@
+# Installation
+
+```bash
+## Commands used for installing the software
+wget https://s3.amazonaws.com/plink1-assets/plink_linux_x86_64_20230116.zip
+unzip plink_linux*.zip
+rm plink_linux*.zip toy.* LICENSE prettify
+
+## Ignore all downloaded/installed files
+echo "plink" > .gitignore
+
+chmod 775 -R .
+chmod 664 README.md
+
+## Version control files
+git add .gitignore
+git add README.md
+```
+
+# Reproducibility
+
+```bash
+## Evaluate the following commands
+module list
+date
+echo "User: ${USER}"
+echo "Node name: ${SLURMD_NODENAME}"
+```
+
+```bash
+
+## copy paste the output from the previous commands below
+```
+Currently Loaded Modules:
+  1) JHPCE_ROCKY9_DEFAULT_ENV   2) JHPCE_tools/3.0
+
+
+
+Sun Sep 24 11:44:37 AM EDT 2023
+User: gpertea1
+Node name: compute-150
+
+```

tensorqtl/1.0.8/README.md

@@ -1,40 +1,40 @@
 # Installation
 
 ```bash
+#   Make sure not to rely on user packages
+export PYTHONNOUSERSITE="not_a_real_path"
+
 ## Commands used for installing the software
 
-#  Create and enter a python virtual environment (we'll actually need R and
-#  some system utilities made available through conda_R/4.3). Note that we're
-#  on the 'caracol' node!
-module load conda_R/4.3
-python -m venv ./tensorqtl_venv
-source tensorqtl_venv/bin/activate
+#  Download tensorQTL 1.0.8 repo to get their requirements.txt suggestion
+wget https://github.com/broadinstitute/tensorqtl/archive/refs/tags/v1.0.8.tar.gz
+tar -xzf v1.0.8.tar.gz
+rm v1.0.8.tar.gz
 
-#  Upgrade pip and install CUDA-aware pytorch
-python -m pip install --upgrade pip
-python -m pip install torch==1.11.0+cu113 -f https://download.pytorch.org/whl/torch_stable.html
+#  Build a conda environment with python, and R (needed for integration with
+#  rpy2)
+source /jhpce/shared/jhpce/core/conda/miniconda3-23.3.1/etc/profile.d/conda.sh
+conda create -y -p $PWD/tensorqtl_env -c conda-forge mamba
+conda activate $PWD/tensorqtl_env
+mamba install -y -c anaconda python==3.8.5
+mamba install -y -c conda-forge r-base==4.2.0
 
-#  Install tensorQTL 1.0.8 (The git repo doesn't have a 1.0.8 release yet, so
-#  we'll clone the latest commit)
-git clone [email protected]:broadinstitute/tensorqtl.git
-cd tensorqtl
-git checkout 890f32977f36d7e5be2d0820c7f382764617b553
+#  Install their recommended python dependencies, a version of PyTorch
+#  compatible with our CUDA/ GPU hardware, and the tensorQTL package itself
+pip install torch==1.11.0+cu113 -f https://download.pytorch.org/whl/torch_stable.html
+pip install -r tensorqtl-1.0.8/install/requirements.txt
 
-#  Despite not explicitly installing tensorqtl==1.0.8 (which isn't available
-#  from pip yet!), it does appear to be installed as a dependency at version
-#  1.0.8
-python -m pip install -r install/requirements.txt
+pip install tensorqtl==1.0.8
 
-#  Exit virtual environment
-deactivate
+conda deactivate
 
 ## Ignore all downloaded/installed files
 echo "tensorqtl*" > .gitignore
 
 #  Allow fairly relaxed permissions, but protect against accidental changes to
-#  the virtual environment
-chmod -R 775 /jhpce/shared/jhpce/libd/tensorqtl/1.0.8
-chmod -R 755 /jhpce/shared/jhpce/libd/tensorqtl/1.0.8/tensorqtl_venv
+#  the conda environment
+chmod -R 775 .
+chmod -R 555 tensorqtl_env
 
 ## Version control files
 git add .gitignore
@@ -48,7 +48,7 @@ git add README.md
 module list
 date
 echo "User: ${USER}"
-echo "Hostname: ${HOSTNAME}"
+echo "Node name: ${SLURMD_NODENAME}"
 ```
 
 ```bash