Mutant peptide ranking for personalized cancer vaccines
Project description
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.
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