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Is your feature request related to a problem? Please describe
All of the following modules:
cat/fastq
custom/tabulartogseacls
custom/tabulartogseagct
gunzip
igv/js
md5sum
shasum
untar
Use the ubuntu container for docker or singularity but a various mix of different conda tools.
conda-forge::coreutils
conda-forge::grep (actually one use the bioconda::grep)
conda-forge::gzip
conda-forge::sed
conda-forge::tar
And given the different tools' versions within the various ubuntu tag (20.04, 22.04 and 24.04), and the different versions of conda recipe available, I cannot use a single ubuntu container to replicate a conda env, and must use a mix of 2 or 3 depending on the actual tool one want to use. Which is bad from a pipeline point of view, as I would rather have the single one container, than 3 different versions of the same.
Second issue, the untar modules, either in conda or in docker/singularity cannot process tar.bz2 files due to the lack of conda-forge::lbzip2.
Describe the solution you'd like
So my suggestion is to create a new image, based on this conda recipe:
Here is the singularity corresponding to it in Seqera containers: oras://community.wave.seqera.io/library/coreutils_grep_gzip_lbzip2_pruned:e1e4ff8dd129544f
and the docker one: community.wave.seqera.io/library/coreutils_grep_gzip_lbzip2_pruned:10736d98b4d693d8, which I have for now mirrored on quay.io in quay.io/nf-core/coreutils_grep_gzip_lbzip2_pruned:10736d98b4d693d8.
Describe alternatives you've considered
No response
Additional context
No response
The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem? Please describe
All of the following modules:
cat/fastq
custom/tabulartogseacls
custom/tabulartogseagct
gunzip
igv/js
md5sum
shasum
untar
Use the ubuntu container for docker or singularity but a various mix of different conda tools.
conda-forge::coreutils
conda-forge::grep
(actually one use thebioconda::grep
)conda-forge::gzip
conda-forge::sed
conda-forge::tar
And given the different tools' versions within the various ubuntu tag (
20.04
,22.04
and24.04
), and the different versions of conda recipe available, I cannot use a single ubuntu container to replicate a conda env, and must use a mix of 2 or 3 depending on the actual tool one want to use. Which is bad from a pipeline point of view, as I would rather have the single one container, than 3 different versions of the same.Second issue, the untar modules, either in conda or in docker/singularity cannot process
tar.bz2
files due to the lack ofconda-forge::lbzip2
.Describe the solution you'd like
So my suggestion is to create a new image, based on this conda recipe:
Here is the singularity corresponding to it in Seqera containers:
oras://community.wave.seqera.io/library/coreutils_grep_gzip_lbzip2_pruned:e1e4ff8dd129544f
and the docker one:
community.wave.seqera.io/library/coreutils_grep_gzip_lbzip2_pruned:10736d98b4d693d8
, which I have for now mirrored on quay.io inquay.io/nf-core/coreutils_grep_gzip_lbzip2_pruned:10736d98b4d693d8
.Describe alternatives you've considered
No response
Additional context
No response
The text was updated successfully, but these errors were encountered: