- recipe seacr
SEACR is intended to call peaks and enriched regions from sparse CUT&RUN or chromatin profiling data in which background is dominated by "zeroes" (i.e. regions with no read coverage). It requires R (https://www.r-project.org) and Bedtools (https://bedtools.readthedocs.io/en/latest/) to be available in your path, and it requires bedgraphs from paired-end sequencing as input, which can be generated from read pair BED files (i.e. BED coordinates reflecting the 5' and 3' termini of each read pair) using bedtools genomecov with the "-bg" flag, or alternatively from name-sorted paired-end BAM files as described in "Preparing input bedgraph files" below.
- Homepage:
- License:
- Recipe:
- package seacr¶
- Versions:
1.3-2,1.3-1,1.3-0,1.1-0- Depends:
on r-base
- 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 seacr
to add into an existing workspace instead, run:
pixi add seacr
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 seacr
Alternatively, to install into a new environment, run:
conda create -n envname seacr
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/seacr:<tag>
(see seacr/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/seacr/README.html)
