recipe curve-curator

CurveCurator is an open-source analysis platform for any dose-dependent data. It fits a classical 4-parameter equation to estimate effect potency, effect size, and the statistical significance of the observed response. 2D-thresholding efficiently reduces false positives in high-throughput experiments and separates relevant from irrelevant or insignificant hits in an automated and unbiased manner. An interactive dashboard allows users to quickly explore data locally.

Homepage:

https://github.com/kusterlab/curve_curator

License:

Apache-2.0

Recipe:

/curve-curator/meta.yaml

package curve-curator

versions:

0.6.0-0

depends bokeh:

>=3.4.0,<3.8.0

depends numpy:

>=1.25.0,<3.0

depends pandas:

>=2.1.0,<3.0.0

depends pytest:

>=7.4.3,<8.0.0

depends python:

>=3.11,<3.14

depends scipy:

>=1.10.1,<2.0.0

depends statsmodels:

>=0.14.0,<0.15.0

depends tqdm:

>=4.66.1,<5.0.0

requirements:

additional platforms:

Installation

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 curve-curator

and update with::

   mamba update curve-curator

To create a new environment, run:

mamba create --name myenvname curve-curator

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 quay.io/biocontainers/curve-curator:<tag>

(see `curve-curator/tags`_ for valid values for ``<tag>``)

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Link to this page

Render an badge with the following MarkDown:

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