recipe earlgrey

Earl Grey: A fully automated TE curation and annotation pipeline

Homepage:

https://github.com/TobyBaril/EarlGrey

Documentation:

https://github.com/TobyBaril/EarlGrey/blob/main/README.md

License:

OSL-2.1

Recipe:

/earlgrey/meta.yaml

Links:

doi: 10.1093/molbev/msae068

Earl Grey is a full-automated transposable element (TE) annotation pipeline, leveraging the most widely-used tools and combining these with a consensus elongation process (BEAT) to better define de novo consensus sequences when annotating new genome assemblies.

package earlgrey

(downloads) docker_earlgrey

versions:
5.1.0-05.0.3-05.0.0-25.0.0-15.0.0-04.5.0-24.5.0-14.5.0-04.4.5-1

5.1.0-05.0.3-05.0.0-25.0.0-15.0.0-04.5.0-24.5.0-14.5.0-04.4.5-14.4.5-04.4.4-04.4.1-04.4.0-04.3.0-04.2.4-14.2.4-04.2.3-04.1.1-14.1.1-04.1.0-04.0.8-04.0.7-04.0.6-04.0.5-04.0.4-04.0.3-04.0.2-04.0.1-14.0.1-04.0-14.0-03.2.2-03.2.1-03.2-03.1-0

depends bedtools:

depends bioconductor-bsgenome:

depends bioconductor-genomeinfodb:

depends bioconductor-genomeinfodbdata:

depends bioconductor-plyranges:

depends cd-hit:

depends emboss:

depends genometools-genometools:

depends heliano:

depends hmmer:

depends libgcc:

>=13

depends libstdcxx:

>=13

depends ltr_retriever:

depends mafft:

depends mreps:

depends ncls:

0.0.64.*

depends ninja-nj:

depends pandas:

depends parallel:

depends pybedtools:

depends pyfaidx:

depends pyranges:

depends python:

3.9.*

depends r-ape:

depends r-cowplot:

depends r-data.table:

depends r-ggtext:

depends r-magrittr:

depends r-optparse:

depends r-plyr:

depends r-tidyverse:

depends r-viridis:

depends recon:

depends repeatmasker:

4.1.5.*

depends repeatmodeler:

>=2.0.4

depends repeatscout:

depends samtools:

depends trf:

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 earlgrey

and update with::

   mamba update earlgrey

To create a new environment, run:

mamba create --name myenvname earlgrey

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/earlgrey:<tag>

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

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