Package Recipe 'bioconductor-genomicplot'

recipe bioconductor-genomicplot

Plot profiles of next generation sequencing data in genomic features

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/GenomicPlot.html
License:: GPL-2
Recipe:: /bioconductor-genomicplot/meta.yaml

Visualization of next generation sequencing (NGS) data is essential for interpreting high-throughput genomics experiment results. 'GenomicPlot' facilitates plotting of NGS data in various formats (bam, bed, wig and bigwig); both coverage and enrichment over input can be computed and displayed with respect to genomic features (such as UTR, CDS, enhancer), and user defined genomic loci or regions. Statistical tests on signal intensity within user defined regions of interest can be performed and represented as boxplots or bar graphs. Parallel processing is used to speed up computation on multicore platforms. In addition to genomic plots which is suitable for displaying of coverage of genomic DNA (such as ChIPseq data), metagenomic (without introns) plots can also be made for RNAseq or CLIPseq data as well.

package bioconductor-genomicplot¶

Versions:

1.8.1-0, 1.4.0-0, 1.0.0-0

Depends:

on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-complexheatmap >=2.26.0,<2.27.0
on bioconductor-edger >=4.8.0,<4.9.0
on bioconductor-genomation >=1.42.0,<1.43.0
on bioconductor-genomicalignments >=1.46.0,<1.47.0
on bioconductor-genomicfeatures >=1.62.0,<1.63.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-plyranges >=1.30.0,<1.31.0
on bioconductor-rcas >=1.36.0,<1.37.0
on bioconductor-rsamtools >=2.26.0,<2.27.0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on bioconductor-seqinfo >=1.0.0,<1.1.0
on bioconductor-txdbmaker >=1.6.0,<1.7.0
on r-base >=4.5,<4.6.0a0
on r-circlize
on r-cowplot >=1.1.1
on r-dplyr
on r-ggplot2 >=3.3.5
on r-ggplotify
on r-ggpubr
on r-ggsci >=2.9
on r-ggsignif >=0.6.3
on r-scales >=1.2.0
on r-tidyr
on r-venndiagram
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-genomicplot

to add into an existing workspace instead, run:

pixi add bioconductor-genomicplot

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-genomicplot

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-genomicplot

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-genomicplot:<tag>

(see bioconductor-genomicplot/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:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-genomicplot/README.html)