- recipe bioconductor-motifpeeker
Benchmarking Epigenomic Profiling Methods Using Motif Enrichment
- Homepage:
https://bioconductor.org/packages/3.22/bioc/html/MotifPeeker.html
- License:
GPL (>= 3)
- Recipe:
MotifPeeker is used to compare and analyse datasets from epigenomic profiling methods with motif enrichment as the key benchmark. The package outputs an HTML report consisting of three sections: (1. General Metrics) Overview of peaks-related general metrics for the datasets (FRiP scores, peak widths and motif-summit distances). (2. Known Motif Enrichment Analysis) Statistics for the frequency of user-provided motifs enriched in the datasets. (3. De-Novo Motif Enrichment Analysis) Statistics for the frequency of de-novo discovered motifs enriched in the datasets and compared with known motifs.
- package bioconductor-motifpeeker¶
-
- Versions:
1.2.0-0- Depends:
on bioconductor-biocfilecache
>=3.0.0,<3.1.0on bioconductor-biocparallel
>=1.44.0,<1.45.0on bioconductor-biostrings
>=2.78.0,<2.79.0on bioconductor-bsgenome
>=1.78.0,<1.79.0on bioconductor-genomicalignments
>=1.46.0,<1.47.0on bioconductor-genomicranges
>=1.62.0,<1.63.0on bioconductor-iranges
>=2.44.0,<2.45.0on bioconductor-memes
>=1.18.0,<1.19.0on bioconductor-rsamtools
>=2.26.0,<2.27.0on bioconductor-rtracklayer
>=1.70.0,<1.71.0on bioconductor-s4vectors
>=0.48.0,<0.49.0on bioconductor-seqinfo
>=1.0.0,<1.1.0on bioconductor-summarizedexperiment
>=1.40.0,<1.41.0on bioconductor-universalmotif
>=1.28.0,<1.29.0on r-base
>=4.5,<4.6.0a0on r-dplyr
on r-dt
on r-ggplot2
on r-heatmaply
on r-htmltools
on r-htmlwidgets
on r-plotly
on r-purrr
on r-rmarkdown
on r-tidyr
on r-viridis
- Additional platforms:
Installation¶
You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).
Pixi¶
With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:
pixi global install bioconductor-motifpeeker
to add into an existing workspace instead, run:
pixi add bioconductor-motifpeeker
In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:
pixi workspace channel add conda-forge
pixi workspace channel add bioconda
Conda¶
With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:
conda install bioconductor-motifpeeker
Alternatively, to install into a new environment, run:
conda create -n envname bioconductor-motifpeeker
with envname being the name of the desired environment.
Container¶
Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:
docker pull quay.io/biocontainers/bioconductor-motifpeeker:<tag>
(see bioconductor-motifpeeker/tags for valid values for <tag>).
Integrated deployment¶
Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.
Download stats¶
Link to this page¶
Render an badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-motifpeeker/README.html)