recipe mmseqs2

MMseqs2: ultra fast and sensitive sequence search and clustering suite

Homepage:

https://github.com/soedinglab/mmseqs2

License:

MIT

Recipe:

/mmseqs2/meta.yaml

Links:

doi: 10.1038/nbt.3988, doi: 10.1038/s41467-018-04964-5, doi: 10.1093/bioinformatics/bty1057, doi: 10.1093/bioinformatics/btab184, doi: 10.1101/2024.11.13.623350v1, biotools: mmseqs2, biotools: linclust

package mmseqs2

(downloads) docker_mmseqs2

versions:
16.747c6-116.747c6-015.6f452-315.6f452-215.6f452-115.6f452-014.7e284-214.7e284-114.7e284-0

16.747c6-116.747c6-015.6f452-315.6f452-215.6f452-115.6f452-014.7e284-214.7e284-114.7e284-013.45111-213.45111-113.45111-012.113e3-212.113e3-112.113e3-011.e1a1c-010.6d92c-09.d36de-08.fac81-17.4e23d-16.f5a1c-15.9375b-14.bff50-14.0b8cc-13.be8f6-13.be8f6-02.23394-0

depends _openmp_mutex:

>=4.5

depends aria2:

depends bzip2:

>=1.0.8,<2.0a0

depends gawk:

depends libgcc:

>=13

depends libstdcxx:

>=13

depends libzlib:

>=1.3.1,<2.0a0

depends perl:

>=5.32.1,<5.33.0a0 *_perl5

depends wget:

depends zlib:

requirements:

additional platforms:
linux-aarch64osx-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 mmseqs2

and update with::

   mamba update mmseqs2

To create a new environment, run:

mamba create --name myenvname mmseqs2

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/mmseqs2:<tag>

(see `mmseqs2/tags`_ for valid values for ``<tag>``)

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