- recipe amalgkit
Tools for transcriptome amalgamation
- Homepage:
- License:
MIT
- Recipe:
- package amalgkit¶
- Versions:
0.16.25-0,0.14.0-0,0.12.20-0,0.12.19-0,0.12.18-0,0.12.17-0,0.12.16-0,0.12.15-0- Depends:
on biopython
on ete4
on fastp
on kallisto
on matplotlib-base
on numpy
on pandas
on python
>=3.9on scikit-learn
on scipy
on seqkit
on sra-tools
>=3on statsmodels
- Additional platforms:
Installation¶
You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).
Pixi¶
With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:
pixi global install amalgkit
to add into an existing workspace instead, run:
pixi add amalgkit
In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:
pixi workspace channel add conda-forge
pixi workspace channel add bioconda
Conda¶
With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:
conda install amalgkit
Alternatively, to install into a new environment, run:
conda create -n envname amalgkit
with envname being the name of the desired environment.
Container¶
Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:
docker pull quay.io/biocontainers/amalgkit:<tag>
(see amalgkit/tags for valid values for <tag>).
Integrated deployment¶
Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.
Download stats
.. Create all the necessary plots for each package by loading all the correct specs and data. Important points on the place and implementation of this script block: 1. It is here, and not in a separate HTML file, as it needs to have the `package.name` rendered in for each package. 2. All packages are handled in one `window.onload` function, as multiple instances of this throughout a (rendered) HTML just overwrite each other.Notes¶
- Optional runtime dependencies:
- inmoose: required for `amalgkit finalize --batch_effect_alg combatseq` - oarfish: required for `amalgkit quant --quant_backend oarfish` - mmseqs2: required for `amalgkit getfastq --rrna_filter yes` or `--contam_filter yes` - busco: required for `amalgkit busco --tool busco` - compleasm: required for `amalgkit busco --tool compleasm`, or selected `--tool auto`
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/amalgkit/README.html)
