- recipe bioconductor-qusage
qusage: Quantitative Set Analysis for Gene Expression
- Homepage:
https://bioconductor.org/packages/3.20/bioc/html/qusage.html
- License:
GPL (>= 2)
- Recipe:
- Links:
biotools: qusage
This package is an implementation the Quantitative Set Analysis for Gene Expression (QuSAGE) method described in (Yaari G. et al, Nucl Acids Res, 2013). This is a novel Gene Set Enrichment-type test, which is designed to provide a faster, more accurate, and easier to understand test for gene expression studies. qusage accounts for inter-gene correlations using the Variance Inflation Factor technique proposed by Wu et al. (Nucleic Acids Res, 2012). In addition, rather than simply evaluating the deviation from a null hypothesis with a single number (a P value), qusage quantifies gene set activity with a complete probability density function (PDF). From this PDF, P values and confidence intervals can be easily extracted. Preserving the PDF also allows for post-hoc analysis (e.g., pair-wise comparisons of gene set activity) while maintaining statistical traceability. Finally, while qusage is compatible with individual gene statistics from existing methods (e.g., LIMMA), a Welch-based method is implemented that is shown to improve specificity. The QuSAGE package also includes a mixed effects model implementation, as described in (Turner JA et al, BMC Bioinformatics, 2015), and a meta-analysis framework as described in (Meng H, et al. PLoS Comput Biol. 2019). For questions, contact Chris Bolen (cbolen1@gmail.com) or Steven Kleinstein (steven.kleinstein@yale.edu)
- package bioconductor-qusage¶
- Versions:
2.44.0-0,2.40.0-0,2.36.0-0,2.34.0-0,2.32.0-0,2.28.0-0,2.26.0-0,2.24.0-1,2.24.0-0,2.44.0-0,2.40.0-0,2.36.0-0,2.34.0-0,2.32.0-0,2.28.0-0,2.26.0-0,2.24.0-1,2.24.0-0,2.22.0-0,2.20.0-0,2.18.0-1,2.16.1-0,2.16.0-0,2.14.0-0,2.12.0-0,2.10.0-0- Depends:
on bioconductor-biobase
>=2.70.0,<2.71.0on bioconductor-limma
>=3.66.0,<3.67.0on r-base
>=4.5,<4.6.0a0on r-emmeans
on r-fftw
on r-nlme
- 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-qusage
to add into an existing workspace instead, run:
pixi add bioconductor-qusage
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-qusage
Alternatively, to install into a new environment, run:
conda create -n envname bioconductor-qusage
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-qusage:<tag>
(see bioconductor-qusage/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¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-qusage/README.html)
