recipe bioconductor-hermes

Preprocessing, analyzing, and reporting of RNA-seq data

Homepage:

https://bioconductor.org/packages/3.17/bioc/html/hermes.html

License:

Apache License 2.0 | file LICENSE

Recipe:

/bioconductor-hermes/meta.yaml

Provides classes and functions for quality control, filtering, normalization and differential expression analysis of pre-processed RNA-seq data. Data can be imported from `SummarizedExperiment` as well as `matrix` objects and can be annotated from BioMart. Filtering for genes without too low expression or containing required annotations, as well as filtering for samples with sufficient correlation to other samples or total number of reads is supported. The standard normalization methods including `cpm`, `rpkm` and `tpm` can be used, and `DESeq2` as well as `voom` differential expression analyses are available.

package bioconductor-hermes

(downloads) docker_bioconductor-hermes

versions:

1.4.0-01.2.0-0

depends bioconductor-biobase:

>=2.60.0,<2.61.0

depends bioconductor-biocgenerics:

>=0.46.0,<0.47.0

depends bioconductor-biomart:

>=2.56.0,<2.57.0

depends bioconductor-complexheatmap:

>=2.16.0,<2.17.0

depends bioconductor-deseq2:

>=1.40.0,<1.41.0

depends bioconductor-edger:

>=3.42.0,<3.43.0

depends bioconductor-genomicranges:

>=1.52.0,<1.53.0

depends bioconductor-iranges:

>=2.34.0,<2.35.0

depends bioconductor-limma:

>=3.56.0,<3.57.0

depends bioconductor-multiassayexperiment:

>=1.26.0,<1.27.0

depends bioconductor-s4vectors:

>=0.38.0,<0.39.0

depends bioconductor-summarizedexperiment:

>=1.30.0,<1.31.0

depends r-assertthat:

depends r-base:

>=4.3,<4.4.0a0

depends r-checkmate:

>=2.1

depends r-circlize:

depends r-dplyr:

depends r-envstats:

depends r-forcats:

depends r-ggfortify:

depends r-ggplot2:

depends r-ggrepel:

>=0.9

depends r-lifecycle:

depends r-magrittr:

depends r-matrixstats:

depends r-purrr:

depends r-r6:

depends r-rdpack:

depends r-rlang:

depends r-tidyr:

requirements:

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-hermes

and update with::

   mamba update bioconductor-hermes

To create a new environment, run:

mamba create --name myenvname bioconductor-hermes

with myenvname being 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-hermes:<tag>

(see `bioconductor-hermes/tags`_ for valid values for ``<tag>``)

Download stats