index.qmd

---
title: "SLE-autoantibody-prediction"
---

![](https://ars.els-cdn.com/content/image/1-s2.0-S0198885922000702-gr1.jpg){fig-align="center"}

This research project aims to predict diagnosis of [Systemic Lupus Erythematosus](https://en.wikipedia.org/wiki/Systemic_lupus_erythematosus) using machine learning and microarray measurements of auto-antibodies . The (python) code [is available on GitHub](https://github.com/umcu/SLE-autoantibody-prediction) and belongs to the following publication:

Brunekreef TE, Reteig LC, Limper M, Haitjema S, Dias J, Mathsson-Alm L, van Laar JM, Otten HG. [Microarray analysis of autoantibodies can identify future Systemic Lupus Erythematosus patients. Human Immunology](https://doi.org/10.1016/j.humimm.2022.03.010). 2022 Jun 1;83(6):509-14.

## Contents

The navigation bar on the left links to all the computational notebooks with the analyses and results for this project. The [Main Results](notebooks/Main Results.ipynb) notebook contains all the results that are reported in the paper. The other notebooks contain all the (exploratory) analyses that we ran (for which we were able to publish the code).

There's also a [project package](https://github.com/umcu/SLE-autoantibody-prediction/tree/main/src/sle) with a number of python modules containing supporting code that are imported in the notebooks.

The original patient data were not shared along with the publication. If you don't have access to this data, but would still like to run the code, the notebooks offer the option to generate some simple synthetic data.

## Reproducibility

1. You'll need either the `conda` or the `mamba` package manager to recreate the computational environment. It might take `conda` a while to resolve the environment in `environment.yml` (see step 3), so it's recommended to use mamba instead.

    If you already have `conda` installed, you can install mamba as follows:

    ```zsh
    conda install mamba -n base -c conda-forge
    ```

    If you don't have conda, you can skip it and [install `mambaforge`](https://github.com/conda-forge/miniforge#mambaforge) instead:

    ```zsh
    wget "https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-$(uname)-$(uname -m).sh"
    bash Mambaforge-$(uname)-$(uname -m).sh
    ```
2. Clone this repo, e.g.: 

    ```zsh
    git clone https://github.com/umcu/SLE-autoantibody-prediction
    cd SLE-autoantibody-prediction
    ```
3. Make and activate the virtual environment, e.g.:

    ```zsh
    mamba env create -f environment.yaml
    conda activate SLE
    ```
4. Install the project package, e.g.

    ```zsh
    pip install -e .
    ```
5. Open and run any of the notebooks, for instance with JupyterLab:

    ```zsh
    jupyter lab
    ```