- recipe bioconductor-pram
Pooling RNA-seq datasets for assembling transcript models
GPL (>= 3)
Publicly available RNA-seq data is routinely used for retrospective analysis to elucidate new biology. Novel transcript discovery enabled by large collections of RNA-seq datasets has emerged as one of such analysis. To increase the power of transcript discovery from large collections of RNA-seq datasets, we developed a new R package named Pooling RNA-seq and Assembling Models (PRAM), which builds transcript models in intergenic regions from pooled RNA-seq datasets. This package includes functions for defining intergenic regions, extracting and pooling related RNA-seq alignments, predicting, selected, and evaluating transcript models.
- package bioconductor-pram¶
- depends bioconductor-biocgenerics:
- depends bioconductor-biocparallel:
- depends bioconductor-genomeinfodb:
- depends bioconductor-genomicalignments:
- depends bioconductor-genomicranges:
- depends bioconductor-iranges:
- depends bioconductor-rsamtools:
- depends bioconductor-rtracklayer:
- depends bioconductor-s4vectors:
- depends r-base:
- depends r-data.table:
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-pram and update with:: mamba update bioconductor-pram
To create a new environment, run:
mamba create --name myenvname bioconductor-pram
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-pram:<tag> (see `bioconductor-pram/tags`_ for valid values for ``<tag>``)