- recipe perl-fastx-abi
FASTX::Abi - Read Sanger trace file (.ab1 chromatograms) in FASTQ format. For traces called with hetero option, the ambiguities will be split into two sequences to allow usage from NGS tools that usually do not understand IUPAC ambiguities.
- Homepage:
- Documentation:
- License:
MIT
- Recipe:
This module reads a Sanger trace (chromatogram). If the chromatogram was saved in "hetero" mode, that is allowing IUPAC ambiguities in the basecalling, the module will return two (unphased) sequences in standard "ACGT" alphabet.
- package perl-fastx-abi¶
- Versions:
1.0.1-1,1.0.1-0,1.0.0-0,0.11-1,0.11-0,0.08-0- Depends:
on perl
>=5.32.1,<6.0a0 *_perl5on perl-bio-trace-abif
on perl-carp
- 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 perl-fastx-abi
to add into an existing workspace instead, run:
pixi add perl-fastx-abi
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 perl-fastx-abi
Alternatively, to install into a new environment, run:
conda create -n envname perl-fastx-abi
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/perl-fastx-abi:<tag>
(see perl-fastx-abi/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 
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