- recipe bioconductor-nbamseq
Negative Binomial Additive Model for RNA-Seq Data
High-throughput sequencing experiments followed by differential expression analysis is a widely used approach to detect genomic biomarkers. A fundamental step in differential expression analysis is to model the association between gene counts and covariates of interest. NBAMSeq a flexible statistical model based on the generalized additive model and allows for information sharing across genes in variance estimation.
- package bioconductor-nbamseq¶
- depends bioconductor-biocparallel:
- depends bioconductor-deseq2:
- depends bioconductor-genefilter:
- depends bioconductor-s4vectors:
- depends bioconductor-summarizedexperiment:
- depends r-base:
- depends r-mgcv:
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-nbamseq and update with:: mamba update bioconductor-nbamseq
To create a new environment, run:
mamba create --name myenvname bioconductor-nbamseq
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-nbamseq:<tag> (see `bioconductor-nbamseq/tags`_ for valid values for ``<tag>``)