# Tag Info

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I was able to reproduce your problem, even in a blank environment. $conda create -n test$ conda activate test $conda install bioconda::blast=2.7.1 Solving environment: failed PackagesNotFoundError: The following packages are not available from current channels: - bioconda::blast=2.7.1 - boost=1.64 - bioconda::blast=2.7.1 - gnutls - bioconda::... 7 These appear to be two separate collections of tools. The conda version is a collection of python scripts whereas the apt version is based on a C library. So, as you might expect, the python version does not have a gt binary. They also have separate GitHub accounts conda genometools vs apt genometools. 7 To my knowledge there's no single listing of the licenses, but you can: conda list | awk '{if(NR>3) printf("%s=%s",$1, $2)}' | xargs conda info | grep license Allegedly conda info --license should work, but at least in conda 4.6.3 it doesn't show any license information. It unfortunate that there's no convenient way to get a tabular list of package:... 5 A good practice is to provide yml file along with your Snakefile. This file should contain all the enviroment definitions that are needed to run your pipeline. The minimum content of this file would be to install snakemake itself. Any other program used in your pipeline should be included as well. For reproducibility version numbers must be used. So, if ... 4 Using only the --use-conda directive, snakemake copies environments somewhere in the local .snakemake directory. This is repeated for each directory you run it in and replicates all environments effectively for each dataset. You can however tell snakemake to use a shared environment location using --conda-prefix as described here: Specify a directory in ... 4 # Install the BiocManager package first install.packages("BiocManager") library("BiocManager") # Then install the Gviz package BiocManager::install("Gviz") 3 Did you try following the installation instructions? Try this in R: source("https://bioconductor.org/biocLite.R") BiocInstaller::biocLite(c("Gviz")) 3 Devon will probably add a more precise answer, until then I just link his Tweet from last week: https://twitter.com/dpryan79/status/1394714988720308226 Edit: 31.5.21 Rollout started yesterday, should take a week to complete: https://twitter.com/dpryan79/status/1399273322601459712 2 I started the roll-out on the 30th in the evening. There's not much of a delay for the October Bioconductor release, but for the summer release we first have to build the newest R version and then rebuild all conda CRAN packages. It's probably not widely known, but Bioconductor packages are only compatible with a single R version. For example, the ones being ... 2 I created a file .condarc in my home directory with the following content: channels: - conda-forge - bioconda - defaults and it works now. I don't understand why this is necessary though. I thought the channels in the .condarc file would be used if I did not specify them in my command. 1 This one uses JQ for parsing and querying conda generated json output (https://stedolan.github.io/jq/) conda list | awk '{if(NR>3) printf("%s=%s\n",$1, \$2)}' | xargs -I{} conda search --info --json "{}" | jq --raw-output '.[][0] | "\(.name)\t\(.version)\t\(.license)"' builds the list, asks conda search for all info on package as json, feeds json to JQ, ...

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The Dockerfile is generated by galaxy-utils, so I'm not entirely sure what it looks like. However you should be able to generate such a "mulled" container as documented here. In short, something of the form: mulled-build build 'bioconductor-csaw=someversion--somebuildnumber' 'someotherpackage=someversion--somebuildnumber' ... That probably ...

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The benefit of using the conda package is that you no longer need to know or care exactly where the jar files are (that many java-based packages require this is TERRIBLE design). The example java -jar ... command in your post becomes: Clustering derep -m '#=GC_RF' -o derep.fa all_seqs.ids all_seqs.samples alignment/*.fasta in the bioconda version. In ...

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Short answer: respect the case of the tool name Longer story below Thanks to terdon, I printed the PATH when the conda environment was active and listed what was in the folder where conda installed the UCSC tool. ls /mnt/home2/miska/cr517/anaconda3/envs/ucsc-netchainsubset377/bin c_rehash libpng-config mysql_config openssl pngfix libpng16-...

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Inside your Snakefile you can provide the same conda: directive to each rule. If you install your pipeline in a central location and have everyone use the same conda when running it (hint: use a wrapper script that sets the path to conda) then everyone will be using the same environment. This has the added benefit that you can make this readable to everyone, ...

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Use BiocManager::install() # Code if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("Gviz", version = "3.8") However, If R < 3.5.0 , please use the following for installing Bioconductor packages. BiocInstaller::biocLite("Gviz")

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This time conda uninstall hmmer in the root environment did the job. The sequence of commands that led me there is shown below. Thanks Devon Ryan. conda list | grep hmmer hmmer 3.1b2 3 bioconda conda uninstall hmmer Solving environment: done ## Package Plan ## environment location: /Users/user/anaconda ...

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