- recipe bioconductor-hilda
Conducting statistical inference on comparing the mutational exposures of mutational signatures by using hierarchical latent Dirichlet allocation
- Homepage:
- License:
GPL-3
- Recipe:
A package built under the Bayesian framework of applying hierarchical latent Dirichlet allocation. It statistically tests whether the mutational exposures of mutational signatures (Shiraishi-model signatures) are different between two groups. The package also provides inference and visualization.
- package bioconductor-hilda¶
- versions:
1.20.0-0,1.16.0-0,1.14.0-0,1.12.0-1,1.12.0-0,1.8.0-2,1.8.0-1,1.8.0-0,1.6.0-0,1.20.0-0,1.16.0-0,1.14.0-0,1.12.0-1,1.12.0-0,1.8.0-2,1.8.0-1,1.8.0-0,1.6.0-0,1.4.0-2,1.4.0-1,1.4.0-0,1.2.0-0,1.0.0-0- depends bioconductor-biocgenerics:
>=0.52.0,<0.53.0- depends bioconductor-biocgenerics:
>=0.52.0,<0.53.0a0- depends bioconductor-biostrings:
>=2.74.0,<2.75.0- depends bioconductor-biostrings:
>=2.74.0,<2.75.0a0- depends bioconductor-bsgenome.hsapiens.ucsc.hg19:
>=1.4.0,<1.5.0- depends bioconductor-bsgenome.hsapiens.ucsc.hg19:
>=1.4.3,<1.5.0a0- depends bioconductor-genomicfeatures:
>=1.58.0,<1.59.0- depends bioconductor-genomicfeatures:
>=1.58.0,<1.59.0a0- depends bioconductor-genomicranges:
>=1.58.0,<1.59.0- depends bioconductor-genomicranges:
>=1.58.0,<1.59.0a0- depends bioconductor-s4vectors:
>=0.44.0,<0.45.0- depends bioconductor-s4vectors:
>=0.44.0,<0.45.0a0- depends bioconductor-txdb.hsapiens.ucsc.hg19.knowngene:
>=3.2.0,<3.3.0- depends bioconductor-txdb.hsapiens.ucsc.hg19.knowngene:
>=3.2.2,<3.3.0a0- depends bioconductor-xvector:
>=0.46.0,<0.47.0- depends bioconductor-xvector:
>=0.46.0,<0.47.0a0- depends libblas:
>=3.9.0,<4.0a0- depends libgcc:
>=13- depends liblapack:
>=3.9.0,<4.0a0- depends libstdcxx:
>=13- depends r-abind:
- depends r-base:
>=4.4,<4.5.0a0- depends r-cowplot:
- depends r-forcats:
- depends r-ggplot2:
- depends r-r2jags:
- depends r-rcpp:
- depends r-stringr:
- depends r-tidyr:
- requirements:
- additional platforms:
Installation
You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).
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-hilda and update with:: mamba update bioconductor-hilda
To create a new environment, run:
mamba create --name myenvname bioconductor-hilda
with
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-hilda:<tag> (see `bioconductor-hilda/tags`_ for valid values for ``<tag>``)
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-hilda/README.html)
