Ranked vaccine peptides for personalized cancer immunotherapy
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README.md

Build Status Coverage Status

vaxrank

Selection of mutated protein fragments for therapeutic personalized cancer vaccines.

Usage

vaxrank \
    --vcf test/data/b16.f10/b16.vcf \
    --bam test/data/b16.f10/b16.combined.bam \
    --vaccine-peptide-length 25 \
    --mhc-predictor netmhc \
    --mhc-alleles H2-Kb,H2-Db \
    --padding-around-mutation 5 \
    --output-ascii-report vaccine-peptides.txt \
    --output-pdf-report vaccine-peptides.pdf \
    --output-html-report vaccine-peptides.html

Installation

Vaxrank can be installed using pip:

pip install vaxrank

Note: to generate PDF reports, you first need to install wkhtmltopdf, which you can do (on OS X) like so:

brew install Caskroom/cask/wkhtmltopdf

Development

To install Vaxrank for local development, you may do the below:

git clone git@github.com:hammerlab/vaxrank.git
conda create -q -n vaxrank-dev-env python=3.5.2 numpy scipy nose pandas pylint
source activate vaxrank-dev-env
pip install -r requirements.txt
pip install .
pyensembl install --release 85 --species human
pyensembl install --release 85 --species mouse

You should run the linter and the test suite as you work on Vaxrank (and these will be run automatically by our continuous integration server up on a PR being made).

./lint.sh
nosetests test

The first run of the tests may take a while (8 minutes on a 2016 Macbook Pro) to create the FM index of the proteome, but subsequent tests should take only a few seconds.