AXEL-F - Standalone version 1.0.0
==========================================

Introduction
------------
This package includes AXEL-F prediction tool, which improves epitope prediction by taking account of
both peptide-MHC binding affinities and expression levels of the peptide's source protein.
The collection contains python scripts to run on linux-based environments and Dockerfile that allows
user to create image containing AXEL-F tool.


Prerequisites:
-------------

+ Python 3.6 or higher
  * http://www.python.org/

+ tcsh
  * http://www.tcsh.org/Welcome
    - Under ubuntu: sudo apt-get install tcsh


Installation (Linux environment):
--------------------------------
Unpack the tar.gz files (IEDB_AXELF-VERSION.tar.gz)
Install packages in 'requirements' to install packages that are necessary for AXEL-F.

$ tar -xzvf IEDB_AXELF-VERSION.tar.gz
$ cd axelf
$ pip install -r requirements.txt

Installation (Mac OS or others):
-------------------------------
Under Mac OS, Axelf won't work properly. The workaround is to run docker container for this.
$ tar -xzvf IEDB_AXELF-VERSION.tar.gz
$ cd axelf
$ docker build -t axelf_img .


Example:
-------
* Help command.
python run_axelf.py -h` or `python run_axelf.py --help
container : docker run --rm axelf_img python run_axelf.py --help

* User provides CSV file ('peptide', 'allele', 'tpm').
python run_axelf.py tests/data/input/sample_input.csv
container : docker run --rm axelf_img python run_axelf.py tests/data/input/sample_input.csv

* User provides CSV file without TPM and sets 'tpm_source' as 'tcga'.
python run_axelf.py tests/data/input/sample_input2.csv -s tcga -c CESC
container : docker run --rm axelf_img python run_axelf.py tests/data/input/sample_input2.csv -s tcga -c CESC

* User provides FASTA file with TPM value.
python run_axelf.py tests/data/input/sample_input.fasta --tpm 3.0 -l 8 -a HLA-A*01:01
container : docker run --rm axelf_img python run_axelf.py tests/data/input/sample_input.fasta --tpm 3.0 -l 8 -a HLA-A*01:01

* User provides FASTA file without TPM and sets 'tpm_source' as 'tcga'.
python run_axelf.py tests/data/input/sample_input.fasta -s tcga -c CESC -g TIGAR -l 8 -a HLA-C12:02
container : docker run --rm axelf_img python run_axelf.py tests/data/input/sample_input.fasta -s tcga -c CESC -g TIGAR -l 8 -a HLA-C12:02