recipe bioconductor-gbscleanr

Error correction tool for noisy genotyping by sequencing (GBS) data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/GBScleanR.html

License:

GPL-3 + file LICENSE

Recipe:

/bioconductor-gbscleanr/meta.yaml

GBScleanR is a package for quality check, filtering, and error correction of genotype data derived from next generation sequcener (NGS) based genotyping platforms. GBScleanR takes Variant Call Format (VCF) file as input. The main function of this package is `estGeno()` which estimates the true genotypes of samples from given read counts for genotype markers using a hidden Markov model with incorporating uneven observation ratio of allelic reads. This implementation gives robust genotype estimation even in noisy genotype data usually observed in Genotyping-By-Sequnencing (GBS) and similar methods, e.g. RADseq. The current implementation accepts genotype data of a diploid population at any generation of multi-parental cross, e.g. biparental F2 from inbred parents, biparental F2 from outbred parents, and 8-way recombinant inbred lines (8-way RILs) which can be refered to as MAGIC population.

package bioconductor-gbscleanr

versions:

2.0.2-0,  1.6.0-0,  1.4.4-0,  1.2.0-1,  1.2.0-0

depends bioconductor-gdsfmt:

>=1.42.0,<1.43.0

depends bioconductor-gdsfmt:

>=1.42.0,<1.43.0a0

depends bioconductor-seqarray:

>=1.46.0,<1.47.0

depends bioconductor-seqarray:

>=1.46.0,<1.47.0a0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc:

>=13

depends liblapack:

>=3.9.0,<4.0a0

depends libstdcxx:

>=13

depends r-base:

>=4.4,<4.5.0a0

depends r-expm:

depends r-ggplot2:

depends r-rcpp:

depends r-rcppparallel:

depends r-tidyr:

requirements:

additional platforms:

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 bioconductor-gbscleanr

and update with::

   mamba update bioconductor-gbscleanr

To create a new environment, run:

mamba create --name myenvname bioconductor-gbscleanr

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/bioconductor-gbscleanr:<tag>

(see `bioconductor-gbscleanr/tags`_ for valid values for ``<tag>``)

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