recipe bioconductor-limrots

LimROTS: A Hybrid Method Integrating Empirical Bayes and Reproducibility-Optimized Statistics for Robust Differential Expression Analysis

Homepage:

https://bioconductor.org/packages/3.22/bioc/html/LimROTS.html

License:

GPL (>= 2)

Recipe:

/bioconductor-limrots/meta.yaml

Differential expression analysis is a prevalent method utilised in the examination of diverse biological data. The reproducibility-optimized test statistic (ROTS) modifies a t-statistic based on the data's intrinsic characteristics and ranks features according to their statistical significance for differential expression between two or more groups (f-statistic). Focussing on proteomics and metabolomics, the current ROTS implementation cannot account for technical or biological covariates such as MS batches or gender differences among the samples. Consequently, we developed LimROTS, which employs a reproducibility-optimized test statistic utilising the limma methodology to simulate complex experimental designs. LimROTS is a hybrid method integrating empirical bayes and reproducibility-optimized statistics for robust analysis of proteomics and metabolomics data.

package bioconductor-limrots

(downloads) docker_bioconductor-limrots

Versions:

1.2.8-0

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

  • on bioconductor-limma >=3.66.0,<3.67.0

  • on bioconductor-qvalue >=2.42.0,<2.43.0

  • on bioconductor-s4vectors >=0.48.0,<0.49.0

  • on bioconductor-summarizedexperiment >=1.40.0,<1.41.0

  • on r-base >=4.5,<4.6.0a0

  • on r-dplyr

  • on r-stringr

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-limrots

to add into an existing workspace instead, run:

pixi add bioconductor-limrots

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-limrots

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-limrots

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-limrots:<tag>

(see bioconductor-limrots/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