recipe latentstrainanalysis

Partitioning and analysis methods for large, complex sequence datasets

Homepage

https://github.com/brian-cleary/LatentStrainAnalysis

License

MIT

Recipe

/latentstrainanalysis/meta.yaml

LSA was developed as a pre-assembly tool for partitioning metagenomic reads. It uses a hyperplane hashing function and streaming SVD in order to find covariance relations between k-mers. The code, and the process outline in LSFScripts in particular, have been optimized to scale to massive data sets in fixed memory with a highly distributed computing environment.

package latentstrainanalysis

(downloads) docker_latentstrainanalysis

Versions

0.0.1-1, 0.0.1-0

Depends gensim

Depends numpy

Depends parallel

Depends pyro4

Depends python

>=2.7,<2.8.0a0

Depends scipy

Requirements

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install latentstrainanalysis

and update with:

conda update latentstrainanalysis

or use the docker container:

docker pull quay.io/biocontainers/latentstrainanalysis:<tag>

(see latentstrainanalysis/tags for valid values for <tag>)