recipe bioconductor-weitrix

Tools for matrices with precision weights, test and explore weighted or sparse data

Homepage:

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

License:

LGPL-2.1 | file LICENSE

Recipe:

/bioconductor-weitrix/meta.yaml

Data type and tools for working with matrices having precision weights and missing data. This package provides a common representation and tools that can be used with many types of high-throughput data. The meaning of the weights is compatible with usage in the base R function "lm" and the package "limma". Calibrate weights to account for known predictors of precision. Find rows with excess variability. Perform differential testing and find rows with the largest confident differences. Find PCA-like components of variation even with many missing values, rotated so that individual components may be meaningfully interpreted. DelayedArray matrices and BiocParallel are supported.

package bioconductor-weitrix

versions:

1.14.0-0,  1.12.0-0,  1.10.0-0,  1.6.0-0,  1.4.0-0,  1.2.0-1,  1.2.0-0,  1.0.0-0

depends bioconductor-biocgenerics:

>=0.48.0,<0.49.0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends bioconductor-delayedarray:

>=0.28.0,<0.29.0

depends bioconductor-delayedmatrixstats:

>=1.24.0,<1.25.0

depends bioconductor-limma:

>=3.58.0,<3.59.0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends bioconductor-topconfects:

>=1.18.0,<1.19.0

depends r-assertthat:

depends r-base:

>=4.3,<4.4.0a0

depends r-ckmeans.1d.dp:

depends r-dplyr:

depends r-ggplot2:

depends r-glm2:

depends r-purrr:

depends r-reshape2:

depends r-rhpcblasctl:

depends r-rlang:

depends r-scales:

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-weitrix

and update with::

   mamba update bioconductor-weitrix

To create a new environment, run:

mamba create --name myenvname bioconductor-weitrix

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-weitrix:<tag>

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

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