recipe bioconductor-msqrob2

Robust statistical inference for quantitative LC-MS proteomics

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/msqrob2.html

License:

Artistic-2.0

Recipe:

/bioconductor-msqrob2/meta.yaml

msqrob2 provides a robust linear mixed model framework for assessing differential abundance in MS-based Quantitative proteomics experiments. Our workflows can start from raw peptide intensities or summarised protein expression values. The model parameter estimates can be stabilized by ridge regression, empirical Bayes variance estimation and robust M-estimation. msqrob2's hurde workflow can handle missing data without having to rely on hard-to-verify imputation assumptions, and, outcompetes state-of-the-art methods with and without imputation for both high and low missingness. It builds on QFeature infrastructure for quantitative mass spectrometry data to store the model results together with the raw data and preprocessed data.

package bioconductor-msqrob2

(downloads) docker_bioconductor-msqrob2

Versions:

1.18.0-01.14.0-01.10.0-01.8.0-01.6.0-01.2.0-01.0.0-0

Depends:
  • on bioconductor-biocparallel >=1.44.0,<1.45.0

  • on bioconductor-limma >=3.66.0,<3.67.0

  • on bioconductor-multiassayexperiment >=1.36.0,<1.37.0

  • on bioconductor-qfeatures >=1.20.0,<1.21.0

  • on bioconductor-summarizedexperiment >=1.40.0,<1.41.0

  • on r-base >=4.5,<4.6.0a0

  • on r-codetools

  • on r-lme4

  • on r-mass

  • on r-matrix

  • on r-purrr

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-msqrob2

to add into an existing workspace instead, run:

pixi add bioconductor-msqrob2

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-msqrob2

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-msqrob2

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-msqrob2:<tag>

(see bioconductor-msqrob2/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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