Installing tensorqtl module

installlation

Author

Festus Nyasimi

Published

November 11, 2020

Installing tensorqtl requires pytorch which is based on gpus but there is also a cpu based version.

CRI has set up pytorch for cpus as in a conda environment and that is what I am going to use to set up tensorqtl.

I will install the tensorqtl in im-lab share space for lab use.

Steps for installation

Create a directory for the environment

mkdir -p /gpfs/data/im-lab/nas40t2/bin/envs
cd /gpfs/data/im-lab/nas40t2/bin/envs

Copy the pytorch environment into this new directory and name it tensorqtl
```
cp -r /apps/software/gcc-6.2.0/miniconda3/4.7.10/envs/pytorch-1.4.0-cpu_py37 tensorqtl
```
Now we have the pytorch setup environment next we are going to set up tensorqtl
Checking if requirements are available

Activate the conda environment
```
conda activate /gpfs/data/im-lab/nas40t2/bin/envs/tensorqtl
```
In this environment when you test the pip command its not executable because the environment has python2. We need to upgrade the environment to use python3.
Test the availability of pip and python3 using the following commands
```
python3 --version
pip3 --version
pip --version
```
If you get error then you definitely need to set up these tools
Set up python3

Install python3 which works with the set up pip
```
conda install python==3.8.0
```
Install tensorqtl

Tensorqtl is available from pip
```
pip install tensorqtl
```
Once installation is successful install the dependecies
Install the rpy2 dependency
```
conda install rpy2
```
Test tensorqtl
```
 python3 -m tensorqtl --help
```
Clean up

Conda caches all these packages which consume a lot of disk space. The need to be removed;
```
 conda clean --all
```

NB: This environment is available for lab use. To activate the the environment for use just activate it

  conda activate /gpfs/data/im-lab/nas40t2/bin/envs/tensorqtl

Happy QTL mapping!!!

---
title: Installing tensorqtl module
author: Festus Nyasimi
date: '2020-11-11'
slug: installing-tensorqtl-module
categories:
  - installlation
tags:
  - how to
description: ''
topics: []
---

Installing tensorqtl requires pytorch which is based on gpus but there is also a cpu based version. 

CRI has set up pytorch for cpus as in a conda environment and that is what I am going to use to set up tensorqtl.

I will install the tensorqtl in im-lab share space for lab use. 

## Steps for installation
1. **Create a directory for the environment**

      ```bash
      mkdir -p /gpfs/data/im-lab/nas40t2/bin/envs
      cd /gpfs/data/im-lab/nas40t2/bin/envs
      ```

2. **Copy the pytorch environment into this new directory and name it tensorqtl**

    ```bash
    cp -r /apps/software/gcc-6.2.0/miniconda3/4.7.10/envs/pytorch-1.4.0-cpu_py37 tensorqtl
    ```

    Now we have the pytorch setup environment next we are going to set up tensorqtl

3. **Checking if requirements are available**

    Activate the conda environment

    ```bash
    conda activate /gpfs/data/im-lab/nas40t2/bin/envs/tensorqtl
    ```

    In this environment when you test the **pip** command its not executable because the     environment has python2. We need to upgrade the environment to use **python3**.

4. **Test the availability of pip and python3 using the following commands**

    ```bash
    python3 --version
    pip3 --version
    pip --version
    ```

    If you get error then you definitely need to set up these tools

5. **Set up python3**

    Install python3 which works with the set up pip

    ```bash
    conda install python==3.8.0
    ```

6. **Install tensorqtl**

    Tensorqtl is available from pip

    ```bash
    pip install tensorqtl
    ```

    Once installation is successful install the dependecies

7. **Install the _rpy2_ dependency**

    ```bash 
    conda install rpy2
    ```

8. **Test tensorqtl**

    ```bash
     python3 -m tensorqtl --help
    ```

9. **Clean up**

    Conda caches all these packages which consume a lot of disk space. The need to be removed;

    ```bash
     conda clean --all
    ```

**NB:** This environment is available for lab use. To activate the the environment for use just activate it

  ```bash
    conda activate /gpfs/data/im-lab/nas40t2/bin/envs/tensorqtl
  ```

**_Happy QTL mapping!!!_**