recipe bioconductor-outrider

OUTRIDER - OUTlier in RNA-Seq fInDER

Homepage:

https://bioconductor.org/packages/3.17/bioc/html/OUTRIDER.html

License:

MIT + file LICENSE

Recipe:

/bioconductor-outrider/meta.yaml

Identification of aberrant gene expression in RNA-seq data. Read count expectations are modeled by an autoencoder to control for confounders in the data. Given these expectations, the RNA-seq read counts are assumed to follow a negative binomial distribution with a gene-specific dispersion. Outliers are then identified as read counts that significantly deviate from this distribution. Furthermore, OUTRIDER provides useful plotting functions to analyze and visualize the results.

package bioconductor-outrider

(downloads) docker_bioconductor-outrider

versions:
1.18.1-01.16.0-11.16.0-01.12.0-21.12.0-11.12.0-01.10.0-01.8.0-11.8.0-0

1.18.1-01.16.0-11.16.0-01.12.0-21.12.0-11.12.0-01.10.0-01.8.0-11.8.0-01.6.0-01.4.0-01.2.0-11.0.2-01.0.1-0

depends bioconductor-biocgenerics:

>=0.46.0,<0.47.0

depends bioconductor-biocparallel:

>=1.34.0,<1.35.0

depends bioconductor-deseq2:

>=1.40.0,<1.41.0

depends bioconductor-genomicfeatures:

>=1.52.0,<1.53.0

depends bioconductor-genomicranges:

>=1.52.0,<1.53.0

depends bioconductor-iranges:

>=2.34.0,<2.35.0

depends bioconductor-pcamethods:

>=1.92.0,<1.93.0

depends bioconductor-s4vectors:

>=0.38.0,<0.39.0

depends bioconductor-summarizedexperiment:

>=1.30.0,<1.31.0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc-ng:

>=12

depends liblapack:

>=3.9.0,<4.0a0

depends libstdcxx-ng:

>=12

depends r-base:

>=4.3,<4.4.0a0

depends r-bbmisc:

depends r-data.table:

depends r-generics:

depends r-ggplot2:

depends r-heatmaply:

depends r-matrixstats:

depends r-pheatmap:

depends r-plotly:

depends r-plyr:

depends r-prroc:

depends r-rcolorbrewer:

depends r-rcpp:

depends r-rcpparmadillo:

depends r-reshape2:

depends r-scales:

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 bioconductor-outrider

and update with::

   mamba update bioconductor-outrider

To create a new environment, run:

mamba create --name myenvname bioconductor-outrider

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-outrider:<tag>

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

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