recipe longreadsum

Long read sequencing data quality control tool

Homepage:

https://github.com/WGLab/LongReadSum

Documentation:

https://github.com/WGLab/LongReadSum#readme

License:

MIT

Recipe:

/longreadsum/meta.yaml

A fast and flexible QC tool for long read sequencing data.

package longreadsum

versions:

1.3.1-3,  1.3.1-2,  1.3.1-0,  1.3.0-1,  1.2.0-1,  1.2.0-0,  1.0.2-0

depends hdf5:

>=1.14.3,<1.14.4.0a0

depends htslib:

>=1.21,<1.22.0a0

depends libgcc:

>=13

depends libstdcxx:

>=13

depends libzlib:

>=1.3.1,<2.0a0

depends numpy:

depends plotly:

depends python:

>=3.10,<3.11.0a0

depends python_abi:

3.10.* *_cp310

requirements:

additional platforms:

linux-aarch64,  osx-arm64

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 longreadsum

and update with::

   mamba update longreadsum

To create a new environment, run:

mamba create --name myenvname longreadsum

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/longreadsum:<tag>

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

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