snacc: alignment-free genome comparison utilizing the normalized compression distance

snacc (sequence non-alignment compression & comparison) is a program implementing the normalized compression distance (NCD) specifically for biological data. These distances can be used for clustering, or to rapidly infer phylogenies for large sets of genomes.

Dependencies

• python3
• numpy
• scipy
• pandas
• matplotlib
• sklearn
• py-lz4framed
• click
• tqdm
• biopython

Installation

To install snacc directly you may use:

virtualenv env --python=python3.6 # optional, but recommended to create a clean environment
source env/bin/activate # if using virtualenv, activate the env
pip install git+https://github.com/SweetiePi/snacc

We recommend you create a conda environment for snacc and install through conda. snacc requires Python 3.6, so create a conda environment with the right Python version:

conda create --name snacc python=3.6

And then activate the environment and install snacc:

source activate snacc
conda install -c asweeten snacc

When inside the snacc conda environment, you can verify correct isntallation by running snacc -h.

Examples

1. Most basic usage

snacc [folder with sequences] -o [output name]

2. Intermediate: customize number of threads and compression algorithm

snacc -d [folder with sequences] -o [output name] -n 24 -c gzip

3. Full control

snacc \
--directory [folder with sequences] \
--output [output name] \
--num-threads 24 \
--compression lz4 \
--fast-mode True \
--reverse-compliment False

Output Example

snacc analysis

• Analysis time: 2018-10-14 15:18:17.257619
• Analysis duration: 0:00:26.383997
• Compression method: lz4
• Reverse complement: False
• Burrows-Wheeler transform: False
• Output filepath: test.csv

Version Information

• Python: 3.6.0 (v3.6.0:41df79263a11, Dec 22 2016, 17:23:13) [GCC 4.2.1 (Apple Inc. build 5666) (dot 3)]
• snacc: 0.0.1
• scikit-learn: 0.20.0
• py-lz4framed: 0.12.0
• umap-learn: 0.3.5

Analyzed Files

• /test_dataset/mysteryGenome_1.fasta
• /test_dataset/mysteryGenome_2.fasta