recipe bioconductor-cn.mops

cn.mops - Mixture of Poissons for CNV detection in NGS data

Homepage:

https://bioconductor.org/packages/3.20/bioc/html/cn.mops.html

License:

LGPL (>= 2.0)

Recipe:

/bioconductor-cn.mops/meta.yaml

Links:

biotools: cn.mops

cn.mops (Copy Number estimation by a Mixture Of PoissonS) is a data processing pipeline for copy number variations and aberrations (CNVs and CNAs) from next generation sequencing (NGS) data. The package supplies functions to convert BAM files into read count matrices or genomic ranges objects, which are the input objects for cn.mops. cn.mops models the depths of coverage across samples at each genomic position. Therefore, it does not suffer from read count biases along chromosomes. Using a Bayesian approach, cn.mops decomposes read variations across samples into integer copy numbers and noise by its mixture components and Poisson distributions, respectively. cn.mops guarantees a low FDR because wrong detections are indicated by high noise and filtered out. cn.mops is very fast and written in C++.

package bioconductor-cn.mops

versions:

1.52.0-1,  1.52.0-0,  1.48.0-0,  1.46.0-0,  1.44.0-1,  1.44.0-0,  1.40.0-2,  1.40.0-1,  1.40.0-0, 

1.52.0-1,  1.52.0-0,  1.48.0-0,  1.46.0-0,  1.44.0-1,  1.44.0-0,  1.40.0-2,  1.40.0-1,  1.40.0-0,  1.38.0-0,  1.36.0-1,  1.36.0-0,  1.34.0-0,  1.32.0-0,  1.30.0-1,  1.28.0-0,  1.26.0-0,  1.24.0-0,  1.22.0-0,  1.18.0-1,  1.18.0-0,  1.16.2-0

depends bioconductor-biobase:

>=2.66.0,<2.67.0

depends bioconductor-biobase:

>=2.66.0,<2.67.0a0

depends bioconductor-biocgenerics:

>=0.52.0,<0.53.0

depends bioconductor-biocgenerics:

>=0.52.0,<0.53.0a0

depends bioconductor-genomeinfodb:

>=1.42.0,<1.43.0

depends bioconductor-genomeinfodb:

>=1.42.0,<1.43.0a0

depends bioconductor-genomicranges:

>=1.58.0,<1.59.0

depends bioconductor-genomicranges:

>=1.58.0,<1.59.0a0

depends bioconductor-iranges:

>=2.40.0,<2.41.0

depends bioconductor-iranges:

>=2.40.0,<2.41.0a0

depends bioconductor-rsamtools:

>=2.22.0,<2.23.0

depends bioconductor-rsamtools:

>=2.22.0,<2.23.0a0

depends bioconductor-s4vectors:

>=0.44.0,<0.45.0

depends bioconductor-s4vectors:

>=0.44.0,<0.45.0a0

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

requirements:

additional platforms:

linux-aarch64

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-cn.mops

and update with::

   mamba update bioconductor-cn.mops

To create a new environment, run:

mamba create --name myenvname bioconductor-cn.mops

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-cn.mops:<tag>

(see `bioconductor-cn.mops/tags`_ for valid values for ``<tag>``)

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