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README.md

+# phap - Phage Host Analysis Pipeline
+
+A snakemake workflow that wraps various phage-host prediction tools.
+
+When possible, tools **and** their dependencies are bundled in 
+[Singularity](https://sylabs.io/) containers.
+
+## Current tools
+
+|Tool name (links to source) | Publication/Preprint |
+|:------|:------|
+[RaFAh](https://sourceforge.net/projects/rafah/)|[Coutinho FH. et al. 2020](https://www.biorxiv.org/content/10.1101/2020.09.25.313155v1?rss=1)
+[vHuLK](https://github.com/soedinglab/wish)|[Amgarten D, et al., 2020](https://www.biorxiv.org/content/10.1101/2020.12.06.413476v1)
+
+
+## Installation
+
+### Dependencies
+
+To run the workflow your will need
+- `snakemake > 5.x` (developed with `5.30.1`)
+- `singularity >= 3.6` (developed with `3.6.3`)
+- `biopython >= 1.78` (developed with `1.78`)
+
+### Conda environemnt
+
+It is recommended to use a [conda environment](https://docs.conda.io/projects/conda/en/latest/).
+The file `environment.txt` can be used to recreate the complete environment 
+used during development.
+
+> The provided `environment.txt` contains an explicit list of all packages,
+> produced with `conda list -n hp --explicit > environment.txt` .
+> This ensures all packages are exactly the same versions/builds, so we 
+> minimize the risk of running into dependencies issues
+
+To get a working environment
+```
+$ git clone 
+
+# I am naming it `hp` here, you can call it whatever you like
+# Note the long notation --file flag; -f will not work.
+$ conda create -n hp --file=environment.txt
+
+# Activate it - use the name you gave above, if it is different
+$ conda activate hp
+
+# The (hp) prefix shows we have activated it
+# Check the snakemake version
+(hp) $ snakemake --version
+5.30.1
+```
+
+## Configuration
+
+### Input data
+
+The tools wrapped in this workflow expect phage sequences as input.
+You should try to make sure that the input sequences you want to analyze 
+correspond to phage genomes/contigs (or at least viruses).
+
+You can probably input any valid fasta file but the 
+[GIGO concept](https://en.wikipedia.org/wiki/Garbage_in,_garbage_out) 
+is probably applicable.
+
+
+A separate workflow to identify phage/viral genomes/contigs is 
+[What the Phage](https://github.com/replikation/What_the_Phage).
+
+The current workflow can handle multiple samples. 
+For each sample, **all viral contigs to be analyzed should be provided as a 
+single multifasta** (can be `gz`ipped). 
+A mapping between sample ids and their corresponding fasta file is provided as
+a samplesheet (see below).
+
+### Sample sheet
+
+You must define a samplesheet with two comma (`,`) separated columns and the
+header `sample,fasta`. Values from the `sample` column must be unique and
+are used as sample identifiers. Their corresponding `fasta` values must be
+valid paths to multifasta files with the phage sequences for that sample.
+
+An example
+```
+$ cat samples.csv
+sample,fasta
+s01,/path/to/s01.fna
+s02,/path/to/another.fna.gz
+```
+
+> Note
+> There is no need to follow any convention for the fasta file name to 
+> reflect the sample id. The values in the sample column are the ones to worry
+> about, as these are the ones used as wildcards within the Snakefile.
+
+You can
+- Fill in the location of the samplesheet within the `config.yml`.
+- Drop the file in the workdir - **Attention**: It should be named `samples.csv`
+- Use `snakemake`'s `--config samplesheet=/path/to/my_samples.csv` when
+executing the wofkflow.
+
+### Models and other data dependencies
+
+For these tools there is no need to pre-download and setup anything - all 
+data and software dependencies are pulled with the singularity image.
+
+* RaFaH
+* vHuLK
+
+## Usage
+
+Basic:
+```
+# From within this directory
+# Make sure you have defined a samplesheet
+(hp)$ snakemake --use-singularity -j16
+```
+
+## Output
+
+All output is stored under a `results` directory within the main workdir.
+Results are stored per sample according to the sample ids you provided in the
+sample sheet.
+For each sample, results for each tool are stored in directories named after 
+the tool. An example looks like this:
+```
+results/
+├── A
+│   ├── all_predictions.tsv
+│   ├── rafah
+│   │   ├── A_CDS.faa
+│   │   ├── A_CDS.fna
+│   │   ├── A_CDS.gff
+│   │   ├── A_CDSxMMSeqs_Clusters
+│   │   ├── A_Genomes.fasta
+│   │   ├── A_Genome_to_Domain_Score_Min_Score_50-Max_evalue_1e-05.tsv
+│   │   ├── A_Ranger_Model_3_Predictions.tsv
+│   │   ├── A_Seq_Info.tsv
+│   │   └── predictions.tsv
+│   ├── tmp
+│   │   ├── genomes
+│   │   └── reflist.txt
+│   └── vhulk
+│       ├── predictions.tsv
+│       └── results.csv
+
+```
+
+* `all_predictions.tsv`: Contains the best prediction per contig (rows) for 
+each tool along with its confidence/p-value/whatever single value each tool 
+uses to evaluate its confidence in the prediction.
+An example for three genomes:
+```
+contig  vhulk_pred      vhulk_score     rafah_pred      rafah_score
+NC_005964.2     None    4.068828        Mycoplasma      0.461
+NC_015271.1     Escherichia_coli        1.0301523       Salmonella      0.495
+NC_023719.1     Bacillus        0.0012575098    Bacillus        0.55
+```
+
+### Per tool output
+* `tmp` directory
+  * Contains one fasta file per input genome, along with other intermediate 
+files necessary for a smooth execution of the workflow **and the raw output 
+of vhulk (under genomes/results/)**.
+
+* `rafah`
+  * All files prefixed with `<sample_id>_` are the rafah's raw output
+  * `predictions.tsv`: A selection of the 1st (`Contig`) , 6th 
+(`Predicted_Host`) and 7th (`Predicted_Host_Score`) columns from file 
+`<sample_id>_Seq_Info.tsv`
+
+* `vhulk`
+  * `results.csv`: Copy of the `results/sample/tmp/genomes/results/results.csv`
+  * `predictions.tsv`: A selection of the 1st (`BIN/genome`), 10th (`final_prediction`) 
+11th (`entropy`) columns from file `results.csv`.