- recipe bioconductor-profileplyr
Visualization and annotation of read signal over genomic ranges with profileplyr
- Homepage:
https://bioconductor.org/packages/3.18/bioc/html/profileplyr.html
- License:
GPL (>= 3)
- Recipe:
Quick and straightforward visualization of read signal over genomic intervals is key for generating hypotheses from sequencing data sets (e.g. ChIP-seq, ATAC-seq, bisulfite/methyl-seq). Many tools both inside and outside of R and Bioconductor are available to explore these types of data, and they typically start with a bigWig or BAM file and end with some representation of the signal (e.g. heatmap). profileplyr leverages many Bioconductor tools to allow for both flexibility and additional functionality in workflows that end with visualization of the read signal.
- package bioconductor-profileplyr¶
- versions:
1.18.0-0
,1.16.0-0
,1.14.0-0
,1.10.0-0
,1.8.0-0
,1.6.0-1
,1.6.0-0
,1.4.3-0
,1.2.0-0
,1.18.0-0
,1.16.0-0
,1.14.0-0
,1.10.0-0
,1.8.0-0
,1.6.0-1
,1.6.0-0
,1.4.3-0
,1.2.0-0
,1.0.1-0
- depends bioconductor-biocgenerics:
>=0.48.0,<0.49.0
- depends bioconductor-biocparallel:
>=1.36.0,<1.37.0
- depends bioconductor-chipseeker:
>=1.38.0,<1.39.0
- depends bioconductor-complexheatmap:
>=2.18.0,<2.19.0
- depends bioconductor-enrichedheatmap:
>=1.32.0,<1.33.0
- depends bioconductor-genomeinfodb:
>=1.38.0,<1.39.0
- depends bioconductor-genomicfeatures:
>=1.54.0,<1.55.0
- depends bioconductor-genomicranges:
>=1.54.0,<1.55.0
- depends bioconductor-iranges:
>=2.36.0,<2.37.0
- depends bioconductor-org.hs.eg.db:
>=3.18.0,<3.19.0
- depends bioconductor-org.mm.eg.db:
>=3.18.0,<3.19.0
- depends bioconductor-rgreat:
>=2.4.0,<2.5.0
- depends bioconductor-rsamtools:
>=2.18.0,<2.19.0
- depends bioconductor-rtracklayer:
>=1.62.0,<1.63.0
- depends bioconductor-s4vectors:
>=0.40.0,<0.41.0
- depends bioconductor-soggi:
>=1.34.0,<1.35.0
- depends bioconductor-summarizedexperiment:
>=1.32.0,<1.33.0
- depends bioconductor-txdb.hsapiens.ucsc.hg19.knowngene:
>=3.2.0,<3.3.0
- depends bioconductor-txdb.hsapiens.ucsc.hg38.knowngene:
>=3.18.0,<3.19.0
- depends bioconductor-txdb.mmusculus.ucsc.mm10.knowngene:
>=3.10.0,<3.11.0
- depends bioconductor-txdb.mmusculus.ucsc.mm9.knowngene:
>=3.2.0,<3.3.0
- depends r-base:
>=4.3,<4.4.0a0
- depends r-circlize:
- depends r-dplyr:
- depends r-ggplot2:
- depends r-magrittr:
- depends r-pheatmap:
- depends r-r.utils:
- depends r-rjson:
- depends r-rlang:
- depends r-tidyr:
- depends r-tiff:
- 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-profileplyr and update with:: mamba update bioconductor-profileplyr
To create a new environment, run:
mamba create --name myenvname bioconductor-profileplyr
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-profileplyr:<tag> (see `bioconductor-profileplyr/tags`_ for valid values for ``<tag>``)
Download stats¶
Link to this page¶
Render an badge with the following MarkDown:
[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-profileplyr/README.html)