Package Recipe 'bioconductor-biotmle'

recipe bioconductor-biotmle

Targeted Learning with Moderated Statistics for Biomarker Discovery

Homepage:: https://bioconductor.org/packages/3.20/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:

1.34.0-0, 1.30.0-0, 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,

1.34.0-0, 1.30.0-0, 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:

on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biocparallel >=1.44.0,<1.45.0
on bioconductor-limma >=3.66.0,<3.67.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on r-assertthat
on r-base >=4.5,<4.6.0a0
on r-dplyr
on r-drtmle >=1.0.4
on r-ggplot2
on r-ggsci
on r-superheat
on r-tibble

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-biotmle

to add into an existing workspace instead, run:

pixi add bioconductor-biotmle

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-biotmle

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-biotmle

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-biotmle:<tag>

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

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-biotmle/README.html)