recipe ghostz

GHOSTZ is a highly efficient remote homologue detection tool.

Homepage:

http://www.bi.cs.titech.ac.jp/ghostz

License:

BSD / BSD-2-Clause

Recipe:

/ghostz/meta.yaml

Links:

doi: 10.1093/bioinformatics/btu780, biotools: ghostz

GHOSTZ is a homology search tool which can detect remote homologues like BLAST and is about 200 times more efficient than BLAST by using database subsequence clustering. GHOSTZ outputs search results in the format similar to BLAST-tabular format.

package ghostz

(downloads) docker_ghostz

Versions:
1.0.2-7,  1.0.2-6,  1.0.2-5,  1.0.2-4,  1.0.2-3,  1.0.2-2,  1.0.2-1,  1.0.2-0,  1.0.0-1, 

1.0.2-7,  1.0.2-6,  1.0.2-5,  1.0.2-4,  1.0.2-3,  1.0.2-2,  1.0.2-1,  1.0.2-0,  1.0.0-1,  1.0.0-0

Depends:

  • on _openmp_mutex >=4.5

  • on libgcc >=13

  • on libgomp

  • on libstdcxx >=13

Additional platforms:
linux-aarch64

Installation

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install ghostz

to add into an existing workspace instead, run:

pixi add ghostz

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install ghostz

Alternatively, to install into a new environment, run:

conda create -n envname ghostz

with envname being the name of the desired environment.

Container

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

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

(see ghostz/tags for valid values for <tag>).

Integrated deployment

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

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