Tools for processing phage display data to allow machine learning using hops.
Open a terminal and type:
pip3 install hops_enrich
hops_enrich requires python3. It depends on numpy, scipy, matplotlib, and
fast_dbscan. Once these are installed, open a terminal in a convenient
location on your computer and run:
git clone https://github.com/harmslab/hops_enrich
cd hops_enrich/
sudo python3 setup.py install
After installing, make a directory that has two fastq.gz files holding
Illumina reads for the experiment done in the presence and absence of
competitor. In the example, these are called alone.tar.gz and
competitor.tar.gz. Then run:
hops_enrich alone.tar.gz competitor.tar.gz
This will calculate the enrichment of peptides in the competitor relative to the sample alone. For a full list of options, type:
hops_enrich -h
This will install the following scripts in the console path:
hops_count: count peptides in an Illumina run
hops_cluster: cluster peptides by sequence
hops_enrich: calculate enrichment of peptides between runs