- recipe bioconductor-nnsvg
Scalable identification of spatially variable genes in spatially-resolved transcriptomics data
MIT + file LICENSE
Method for scalable identification of spatially variable genes (SVGs) in spatially-resolved transcriptomics data. The method is based on nearest-neighbor Gaussian processes and uses the BRISC algorithm for model fitting and parameter estimation. Allows identification and ranking of SVGs with flexible length scales across a tissue slide or within spatial domains defined by covariates. Scales linearly with the number of spatial locations and can be applied to datasets containing thousands or more spatial locations.
- package bioconductor-nnsvg¶
- depends bioconductor-biocparallel:
- depends bioconductor-singlecellexperiment:
- depends bioconductor-spatialexperiment:
- depends bioconductor-summarizedexperiment:
- depends r-base:
- depends r-brisc:
- depends r-matrix:
- depends r-matrixstats:
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-nnsvg and update with:: mamba update bioconductor-nnsvg
To create a new environment, run:
mamba create --name myenvname bioconductor-nnsvg
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-nnsvg:<tag> (see `bioconductor-nnsvg/tags`_ for valid values for ``<tag>``)