recipe bioconductor-singlemoleculefootprinting

Analysis tools for Single Molecule Footprinting (SMF) data

Homepage:

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

License:

GPL-3

Recipe:

/bioconductor-singlemoleculefootprinting/meta.yaml

SingleMoleculeFootprinting provides functions to analyze Single Molecule Footprinting (SMF) data. Following the workflow exemplified in its vignette, the user will be able to perform basic data analysis of SMF data with minimal coding effort. Starting from an aligned bam file, we show how to perform quality controls over sequencing libraries, extract methylation information at the single molecule level accounting for the two possible kind of SMF experiments (single enzyme or double enzyme), classify single molecules based on their patterns of molecular occupancy, plot SMF information at a given genomic location.

package bioconductor-singlemoleculefootprinting

versions:

2.0.0-0,  1.10.0-0,  1.8.0-0,  1.6.0-0,  1.2.0-0,  1.0.0-0

depends bioconductor-biocgenerics:

>=0.52.0,<0.53.0

depends bioconductor-biostrings:

>=2.74.0,<2.75.0

depends bioconductor-bsgenome:

>=1.74.0,<1.75.0

depends bioconductor-genomeinfodb:

>=1.42.0,<1.43.0

depends bioconductor-genomicranges:

>=1.58.0,<1.59.0

depends bioconductor-iranges:

>=2.40.0,<2.41.0

depends bioconductor-plyranges:

>=1.26.0,<1.27.0

depends bioconductor-quasr:

>=1.46.0,<1.47.0

depends bioconductor-s4vectors:

>=0.44.0,<0.45.0

depends r-base:

>=4.4,<4.5.0a0

depends r-dplyr:

depends r-ggplot2:

depends r-ggpointdensity:

depends r-ggrepel:

depends r-matrix:

depends r-patchwork:

depends r-plyr:

depends r-rcolorbrewer:

depends r-rlang:

depends r-stringr:

depends r-tibble:

depends r-tidyr:

depends r-tidyverse:

depends r-viridis:

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-singlemoleculefootprinting

and update with::

   mamba update bioconductor-singlemoleculefootprinting

To create a new environment, run:

mamba create --name myenvname bioconductor-singlemoleculefootprinting

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-singlemoleculefootprinting:<tag>

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

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