recipe bioconductor-dinor

Differential NOMe-seq analysis

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/dinoR.html

License:

MIT + file LICENSE

Recipe:

/bioconductor-dinor/meta.yaml

dinoR tests for significant differences in NOMe-seq footprints between two conditions, using genomic regions of interest (ROI) centered around a landmark, for example a transcription factor (TF) motif. This package takes NOMe-seq data (GCH methylation/protection) in the form of a Ranged Summarized Experiment as input. dinoR can be used to group sequencing fragments into 3 or 5 categories representing characteristic footprints (TF bound, nculeosome bound, open chromatin), plot the percentage of fragments in each category in a heatmap, or averaged across different ROI groups, for example, containing a common TF motif. It is designed to compare footprints between two sample groups, using edgeR's quasi-likelihood methods on the total fragment counts per ROI, sample, and footprint category.

package bioconductor-dinor

versions:

1.2.0-0

depends bioconductor-biocgenerics:

>=0.52.0,<0.53.0

depends bioconductor-complexheatmap:

>=2.22.0,<2.23.0

depends bioconductor-edger:

>=4.4.0,<4.5.0

depends bioconductor-genomicranges:

>=1.58.0,<1.59.0

depends bioconductor-summarizedexperiment:

>=1.36.0,<1.37.0

depends r-base:

>=4.4,<4.5.0a0

depends r-circlize:

depends r-cowplot:

depends r-dplyr:

depends r-ggplot2:

depends r-matrix:

depends r-rlang:

depends r-stringr:

depends r-tibble:

depends r-tidyr:

depends r-tidyselect:

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-dinor

and update with::

   mamba update bioconductor-dinor

To create a new environment, run:

mamba create --name myenvname bioconductor-dinor

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-dinor:<tag>

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

Download stats

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