recipe bioconductor-rdisop

Decomposition of Isotopic Patterns

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/Rdisop.html

License:

GPL-2

Recipe:

/bioconductor-rdisop/meta.yaml

In high resolution mass spectrometry (HR-MS), the measured masses can be decomposed into potential element combinations (chemical sum formulas). Where additional mass/intensity information of respective isotopic peaks is available, decomposition can take this information into account to better rank the potential candidate sum formulas. To compare measured mass/intensity information with the theoretical distribution of candidate sum formulas, the latter needs to be calculated. This package implements fast algorithms to address both tasks, the calculation of isotopic distributions for arbitrary sum formulas (assuming a HR-MS resolution of roughly 30,000), and the ranked list of sum formulas fitting an observed peak or isotopic peak set.

package bioconductor-rdisop

(downloads) docker_bioconductor-rdisop

Versions:
1.70.0-0,  1.66.0-0,  1.62.0-1,  1.62.0-0,  1.60.0-0,  1.58.0-2,  1.58.0-1,  1.58.0-0,  1.54.0-2, 

1.70.0-0,  1.66.0-0,  1.62.0-1,  1.62.0-0,  1.60.0-0,  1.58.0-2,  1.58.0-1,  1.58.0-0,  1.54.0-2,  1.54.0-1,  1.54.0-0,  1.52.0-0,  1.50.0-1,  1.50.0-0,  1.48.0-0,  1.46.0-0,  1.44.0-1,  1.44.0-0,  1.42.1-0,  1.42.0-0

Depends:

  • on libblas >=3.9.0,<4.0a0

  • on libgcc >=14

  • on liblapack >=3.9.0,<4.0a0

  • on liblzma >=5.8.2,<6.0a0

  • on libstdcxx >=14

  • on libzlib >=1.3.1,<2.0a0

  • on r-base >=4.5,<4.6.0a0

  • on r-rcpp

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 bioconductor-rdisop

to add into an existing workspace instead, run:

pixi add bioconductor-rdisop

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 bioconductor-rdisop

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-rdisop

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/bioconductor-rdisop:<tag>

(see bioconductor-rdisop/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.

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