recipe bioconductor-biotmle

Targeted Learning with Moderated Statistics for Biomarker Discovery

Homepage:

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

License:

MIT + file LICENSE

Recipe:

/bioconductor-biotmle/meta.yaml

Tools for differential expression biomarker discovery based on microarray and next-generation sequencing data that leverage efficient semiparametric estimators of the average treatment effect for variable importance analysis. Estimation and inference of the (marginal) average treatment effects of potential biomarkers are computed by targeted minimum loss-based estimation, with joint, stable inference constructed across all biomarkers using a generalization of moderated statistics for use with the estimated efficient influence function. The procedure accommodates the use of ensemble machine learning for the estimation of nuisance functions.

package bioconductor-biotmle

versions:

1.26.0-0,  1.24.0-0,  1.22.0-0,  1.18.0-0,  1.16.0-0,  1.14.0-1,  1.14.0-0,  1.12.0-0,  1.10.0-0, 

1.26.0-0,  1.24.0-0,  1.22.0-0,  1.18.0-0,  1.16.0-0,  1.14.0-1,  1.14.0-0,  1.12.0-0,  1.10.0-0,  1.8.0-1,  1.6.0-0

depends bioconductor-biocgenerics:

>=0.48.0,<0.49.0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

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 r-assertthat:

depends r-base:

>=4.3,<4.4.0a0

depends r-dplyr:

depends r-drtmle:

>=1.0.4

depends r-ggplot2:

depends r-ggsci:

depends r-superheat:

depends r-tibble:

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-biotmle

and update with::

   mamba update bioconductor-biotmle

To create a new environment, run:

mamba create --name myenvname bioconductor-biotmle

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-biotmle:<tag>

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

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