- recipe bioconductor-scry
Small-Count Analysis Methods for High-Dimensional Data
Many modern biological datasets consist of small counts that are not well fit by standard linear-Gaussian methods such as principal component analysis. This package provides implementations of count-based feature selection and dimension reduction algorithms. These methods can be used to facilitate unsupervised analysis of any high-dimensional data such as single-cell RNA-seq.
- package bioconductor-scry¶
- depends bioconductor-biocsingular:
- depends bioconductor-delayedarray:
- depends bioconductor-singlecellexperiment:
- depends bioconductor-summarizedexperiment:
- depends r-base:
- depends r-glmpca:
- depends r-matrix:
While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.
Given that you already have a conda environment in which you want to have this package, install with:
mamba install bioconductor-scry and update with:: mamba update bioconductor-scry
To create a new environment, run:
mamba create --name myenvname bioconductor-scry
myenvnamebeing a reasonable name for the environment (see e.g. the mamba docs for details and further options).
Alternatively, use the docker container:
docker pull quay.io/biocontainers/bioconductor-scry:<tag> (see `bioconductor-scry/tags`_ for valid values for ``<tag>``)