README.md

# Integrative Network Fusion (INF)
![INF pipeline ](figs/INF_pipeline.jpeg)

## Setup
```bash
git clone https://gitlab.fbk.eu/MPBA/INF
cd INF
conda env create -f env.yml -n inf
conda activate inf
```

### Additional dependencies

#### R dependencies
To install the R dependencies (not in conda channels), run the following command via the R prompt:
```bash
install.packages("TunePareto")
```

#### MLPY
To install `mlpy` follow this instructions:

`mlpy` package is required for some operations included in the DAP procedure.

The `mlpy` package available on PyPI is outdated and not working on OSX platforms.

These are the steps to follow:

Let `<ANACONDA>` be your anaconda path (e.g., `/home/user/anaconda3`).

Adjust these environmental variables:
```bash
export LD_LIBRARY_PATH=<ANACONDA>/envs/<ENV>/lib:${LD_LIBRARY_PATH}
export CPATH=<ANACONDA>/envs/<ENV>/include:${CPATH}
```

and then install `mlpy` from GitLab:
```bash
pip install git+https://gitlab.fbk.eu/MPBA/mlpy.git
```


## Usage

**Input files**

* omics layer 1 data: samples x features, tab-separated, with row & column names
* omics layer 2 data: same as above (**samples must be in the same order as the first file**)
* omics layers 1+2 data: the juxtaposition of the above two files
* labels file: one column, just the labels, no header (**same order as the data files**)

**Example run**

The INF pipeline is implemented as a Snakefile.

The following directory tree is required:

* {datafolder}/{dataset}/{layer1}_{layer2}_{tr,ts}.txt
* {datafolder}/{dataset}/labels_{target}_{tr,ts}.txt
* {datafolder}/{dataset}/{layer1,layer2}_{tr,ts}.txt
* {outfolder}/{dataset}/{target}/{juxt,rSNF,rSNFi,single}/ _(these will be created if not present)_

All the {variables} can be specified either in a config.yaml file or on the command line; for example:

```{python}
snakemake --config datafolder="data" dataset="breast" target="ER" layer1="gene" layer2="cnv"
```

A maximum number of cores can also be set:

```{python}
snakemake [--config etc.] --cores 12
```

The pipeline can be "dry-run" using the `-n` flag:

```{python}
snakemake --cores 12 -n
```