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BIISQ: Bayesian nonparametric discovery of Isoforms and Individual Specific Quantification
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README.md

README.md

BIISQ

Bayesian nonparametric discovery of Isoforms and Individual Specific Quantification with BIISQ

Installation

Requires python version 2 (2.7+)

installation of required packages

Required packages: joblib cython numpy scipy

for an existing installation of python/anaconda

If you have a working anaconda or python installation, then:

pip install --user numpy
pip install --user scipy
pip install --user joblib
pip install --user cython

for a new installation of Python 2 (2.7+)

If you would like to install via a new vitual environment, then:

VIRT_HOME=/n/fs/biisq/virtenvs
cd $VIRT_HOME
virtualenv biisq_env
source biisq_env/bin/activate

pip install numpy
pip install scipy
pip install cython
pip install joblib

installation of BIISQ

git clone https://github.com/bee-hive/BIISQ.git
cd BIISQ/examples/ex_gene_1/
sh ex_gene_1_run.sh
cd viz
sh run_viz.sh

there is another example for paired end data in BIISQ/examples/paired_end.

Running this script will summarize transcript composition and quantification. By default results will be stored in BIISQ/examples/ex_gene_1/output. The summary.html file contains descriptions of the individuals and isoform compositions.

Running recommendations

If your data is very small, you might consider running BIISQ several times without proposals and merging, e.g. --max-n-prop 0 --min-n-prop 0

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