- recipe r-jackstraw
Test for association between the observed data and their systematic patterns of variations. Systematic patterns may be captured by latent variables using principal component analysis (PCA), factor analysis (FA), and related methods. The jackstraw enables statistical testing for association between observed variables and latent variables, as captured by PCs or other estimates. Similarly, unsupervised clustering, such as K-means clustering, partition around medoids (PAM), and others, finds subpopulations among the observed variables. The jackstraw estimates statistical significance of cluster membership, including unsupervised evaluation of cell identities in single cell RNA-seq. P-values and posterior probabilities allows one to rigorously evaluate the strength of cluster membership assignments.
- Homepage:
- License:
GPL2 / GPL-2.0-only
- Recipe:
- package r-jackstraw¶
- Versions:
1.3.17-0,1.3.9-1,1.3.9-0,1.3.8-1,1.3.8-0,1.3.1-1,1.3.1-0,1.3-6,1.3-5,1.3.17-0,1.3.9-1,1.3.9-0,1.3.8-1,1.3.8-0,1.3.1-1,1.3.1-0,1.3-6,1.3-5,1.3-4,1.3-3,1.3-2,1.3-1,1.3-0- Depends:
on bioconductor-qvalue
on r-base
>=4.4,<4.5.0a0on r-bedmatrix
on r-cluster
on r-clusterr
on r-corpcor
on r-genio
on r-irlba
on r-rsvd
- 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 r-jackstraw
to add into an existing workspace instead, run:
pixi add r-jackstraw
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 r-jackstraw
Alternatively, to install into a new environment, run:
conda create -n envname r-jackstraw
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/r-jackstraw:<tag>
(see r-jackstraw/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/r-jackstraw/README.html)
