biotmle

This is the development version of biotmle; for the stable release version, see biotmle.

Targeted Learning with Moderated Statistics for Biomarker Discovery

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DOI: 10.18129/B9.bioc.biotmle

Bioconductor version: Development (3.23)

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.

Author: Nima Hejazi [aut, cre, cph] ORCID iD ORCID: 0000-0002-7127-2789 , Alan Hubbard [aut, ths] ORCID iD ORCID: 0000-0002-3769-0127 , Mark van der Laan [aut, ths] ORCID iD ORCID: 0000-0003-1432-5511 , Weixin Cai [ctb] ORCID iD ORCID: 0000-0003-2680-3066 , Philippe Boileau [ctb] ORCID iD ORCID: 0000-0002-4850-2507

Maintainer: Nima Hejazi <nh at nimahejazi.org>

Citation (from within R, enter citation("biotmle")):

Installation

To install this package, start R (version "4.6") and enter:


if (!require("BiocManager", quietly = TRUE))
 install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("biotmle")

For older versions of R, please refer to the appropriate Bioconductor release.