recipe sabre

A barcode demultiplexing and trimming tool for FastQ files

Homepage:

https://github.com/najoshi/sabre/

License:

MIT

Recipe:

/sabre/meta.yaml

Next-generation sequencing can currently produce hundreds of millions of reads per lane of sample and that number increases at a dizzying rate. Barcoding individual sequences for multiple lines or multiple species is a cost-efficient method to sequence and analyze a broad range of data. Sabre is a tool that will demultiplex barcoded reads into separate files. It will work on both single-end and paired-end data in fastq format. It simply compares the provided barcodes with each read and separates the read into its appropriate barcode file, after stripping the barcode from the read (and also stripping the quality values of the barcode bases). If a read does not have a recognized barcode, then it is put into the unknown file. Sabre also has an option (-m) to allow mismatches of the barcodes. Sabre also supports gzipped file inputs. Also, since sabre does not use the quality values in any way, it can be used on fasta data that is converted to fastq by creating fake quality values. Finally, after demultiplexing, sabre outputs a summary of how many records went into each barcode file.

package sabre

versions:

1.000-5,  1.000-4,  1.000-3,  1.000-2,  1.000-1,  1.000-0

depends libgcc-ng:

>=12

depends libzlib:

>=1.2.13,<1.3.0a0

depends zlib:

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 sabre

and update with::

   mamba update sabre

To create a new environment, run:

mamba create --name myenvname sabre

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/sabre:<tag>

(see `sabre/tags`_ for valid values for ``<tag>``)

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