recipe chromeister

An ultra fast, heuristic approach to detect conserved signals in extremely large pairwise genome comparisons



GPL / GPL-3.0




doi: 10.1038/s41598-019-46773-w

package chromeister

(downloads) docker_chromeister



depends cycler:

depends kiwisolver:

depends libgcc-ng:


depends numpy:

depends opencv:

depends pillow:

depends pyparsing:

depends python:


depends python-dateutil:

depends r-ape:

depends r-base:

depends scikit-build:

depends six:



You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install chromeister

and update with::

   mamba update chromeister

To create a new environment, run:

mamba create --name myenvname chromeister

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `chromeister/tags`_ for valid values for ``<tag>``)

Download stats