- recipe bioconductor-pathwaypca
Integrative Pathway Analysis with Modern PCA Methodology and Gene Selection
- Homepage:
https://bioconductor.org/packages/3.20/bioc/html/pathwayPCA.html
- License:
GPL-3
- Recipe:
pathwayPCA is an integrative analysis tool that implements the principal component analysis (PCA) based pathway analysis approaches described in Chen et al. (2008), Chen et al. (2010), and Chen (2011). pathwayPCA allows users to: (1) Test pathway association with binary, continuous, or survival phenotypes. (2) Extract relevant genes in the pathways using the SuperPCA and AES-PCA approaches. (3) Compute principal components (PCs) based on the selected genes. These estimated latent variables represent pathway activities for individual subjects, which can then be used to perform integrative pathway analysis, such as multi-omics analysis. (4) Extract relevant genes that drive pathway significance as well as data corresponding to these relevant genes for additional in-depth analysis. (5) Perform analyses with enhanced computational efficiency with parallel computing and enhanced data safety with S4-class data objects. (6) Analyze studies with complex experimental designs, with multiple covariates, and with interaction effects, e.g., testing whether pathway association with clinical phenotype is different between male and female subjects. Citations: Chen et al. (2008) <https://doi.org/10.1093/bioinformatics/btn458>; Chen et al. (2010) <https://doi.org/10.1002/gepi.20532>; and Chen (2011) <https://doi.org/10.2202/1544-6115.1697>.
- package bioconductor-pathwaypca¶
- Versions:
1.26.0-0,1.22.0-0,1.18.0-0,1.16.1-0,1.14.0-0,1.10.0-0,1.8.0-0,1.6.3-0,1.6.0-0,1.26.0-0,1.22.0-0,1.18.0-0,1.16.1-0,1.14.0-0,1.10.0-0,1.8.0-0,1.6.3-0,1.6.0-0,1.4.0-0,1.2.0-0,1.0.0-1- Depends:
on r-base
>=4.5,<4.6.0a0on r-lars
on r-survival
- 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-pathwaypca
to add into an existing workspace instead, run:
pixi add bioconductor-pathwaypca
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-pathwaypca
Alternatively, to install into a new environment, run:
conda create -n envname bioconductor-pathwaypca
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-pathwaypca:<tag>
(see bioconductor-pathwaypca/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-pathwaypca/README.html)
