- recipe tecap
3' terminal exon capture diagnostics for long-read scRNA-seq
- Homepage:
- License:
MIT / MIT
- Recipe:
- Links:
tecap classifies long-read alignments by where their 3' end lands relative to the terminal exon, its UTR, and a polyA site atlas. It decomposes capture failures into nine mechanism buckets and measures reference base composition downstream of each cleavage site to distinguish classic A-tract internal priming from moderate-A priming characteristic of saturating in-solution oligo-dT. Designed for PacBio Iso-Seq / Kinnex and Oxford Nanopore cDNA BAMs. Direct-RNA sequencing is unsupported.
- package tecap¶
- Versions:
0.2.0-0- Depends:
on intervaltree
>=3.1on matplotlib-base
>=3.5on numpy
>=1.22on pysam
>=0.22on python
>=3.9
- 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 tecap
to add into an existing workspace instead, run:
pixi add tecap
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 tecap
Alternatively, to install into a new environment, run:
conda create -n envname tecap
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/tecap:<tag>
(see tecap/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/tecap/README.html)
