/AAV

Scripts for analyzing PacBio AAV sequences

Primary LanguagePythonMIT LicenseMIT

AAV

Last Updated: 05/03/2024

Disclaimer

THIS REPOSITORY IS OBSOLETE AND WILL NO LONGER BE MAINTAINED

This was a personal repository for analyzing PacBio long-read AAV sequencing data. The open source code is now being maintained and developed at FormBio's LAAVA repo. Please visit LAAVA to get the latest code base! Thanks!

Pre-requisites

  • Python 3.7
  • R

Python libaries required:

R packages required:

  • ggplot2
  • dplyr
  • grid
  • gridExtra

Installation

You can directly download/clone the repo to use the scripts directly.

$ git clone https://github.com/Magdoll/AAV.git

You can install the dependencies on your own or use one of the following conda-based options.

Option1: Use Conda and install the pre-requisites individually

conda install -c bioconda pysam
conda install -c r ggplot2
conda install -c r dpylr
conda install -c r grid
conda install -c r gridExtra

Option2: Use Conda with yml

Suppose you have anaconda installed and the binary is in $HOME/anaCogentPy37/bin. You would add the binary to $PATH and create a new conda environment called AAV.env.

$ export PATH=$HOME/anaCogentPy37/bin:$PATH
$ conda env create -f AAV.conda_env.yml
$ source activate AAV.env

At this point the prompt should change to (AAV.env) $

Usage

Please read the AAV tutorial