- recipe bioconductor-lemur
Latent Embedding Multivariate Regression
- Homepage:
- License:
MIT + file LICENSE
- Recipe:
Fit a latent embedding multivariate regression (LEMUR) model to multi-condition single-cell data. The model provides a parametric description of single-cell data measured with treatment vs. control or more complex experimental designs. The parametric model is used to (1) align conditions, (2) predict log fold changes between conditions for all cells, and (3) identify cell neighborhoods with consistent log fold changes. For those neighborhoods, a pseudobulked differential expression test is conducted to assess which genes are significantly changed.
- package bioconductor-lemur¶
-
- Versions:
1.8.0-0,1.4.0-0,1.0.4-0- Depends:
on bioconductor-biocgenerics
>=0.56.0,<0.57.0on bioconductor-biocgenerics
>=0.56.0,<0.57.0a0on bioconductor-biocneighbors
>=2.4.0,<2.5.0on bioconductor-biocneighbors
>=2.4.0,<2.5.0a0on bioconductor-delayedmatrixstats
>=1.32.0,<1.33.0on bioconductor-delayedmatrixstats
>=1.32.0,<1.33.0a0on bioconductor-glmgampoi
>=1.22.0,<1.23.0on bioconductor-glmgampoi
>=1.22.0,<1.23.0a0on bioconductor-hdf5array
>=1.38.0,<1.39.0on bioconductor-hdf5array
>=1.38.0,<1.39.0a0on bioconductor-limma
>=3.66.0,<3.67.0on bioconductor-limma
>=3.66.0,<3.67.0a0on bioconductor-matrixgenerics
>=1.22.0,<1.23.0on bioconductor-matrixgenerics
>=1.22.0,<1.23.0a0on bioconductor-s4vectors
>=0.48.0,<0.49.0on bioconductor-s4vectors
>=0.48.0,<0.49.0a0on bioconductor-singlecellexperiment
>=1.32.0,<1.33.0on bioconductor-singlecellexperiment
>=1.32.0,<1.33.0a0on bioconductor-summarizedexperiment
>=1.40.0,<1.41.0on bioconductor-summarizedexperiment
>=1.40.0,<1.41.0a0on libblas
>=3.9.0,<4.0a0on libgcc
>=14on liblapack
>=3.9.0,<4.0a0on liblzma
>=5.8.2,<6.0a0on libstdcxx
>=14on libzlib
>=1.3.1,<2.0a0on r-base
>=4.5,<4.6.0a0on r-harmony
>=1.2.0on r-irlba
on r-matrix
on r-matrixstats
on r-rcpp
on r-rcpparmadillo
on r-rlang
>=1.1.0on r-vctrs
>=0.6.0
- 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-lemur
to add into an existing workspace instead, run:
pixi add bioconductor-lemur
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-lemur
Alternatively, to install into a new environment, run:
conda create -n envname bioconductor-lemur
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-lemur:<tag>
(see bioconductor-lemur/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-lemur/README.html)