biotmle

DOI: 10.18129/B9.bioc.biotmle    

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

Targeted Learning with Moderated Statistics for Biomarker Discovery

Bioconductor version: Development (3.12)

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] , Alan Hubbard [aut, ths] , Mark van der Laan [aut, ths] , Weixin Cai [ctb]

Maintainer: Nima Hejazi <nh at nimahejazi.org>

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

Installation

To install this package, start R (version "4.0") and enter:

if (!requireNamespace("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.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("biotmle")

 

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PDF   Reference Manual
Text   NEWS
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Details

biocViews DifferentialExpression, GeneExpression, ImmunoOncology, Microarray, RNASeq, Regression, Sequencing, Software
Version 1.13.0
In Bioconductor since BioC 3.5 (R-3.4) (3 years)
License file LICENSE
Depends R (>= 3.4)
Imports stats, methods, dplyr, tibble, ggplot2, ggsci, superheat, assertthat, future, doFuture, drtmle (>= 1.0.4), S4Vectors, BiocGenerics, BiocParallel, SummarizedExperiment, limma
LinkingTo
Suggests testthat, knitr, rmarkdown, BiocStyle, arm, earth, xgboost, SuperLearner, Matrix, DBI, biotmleData(>= 1.1.1)
SystemRequirements
Enhances
URL https://code.nimahejazi.org/biotmle
BugReports https://github.com/nhejazi/biotmle/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package biotmle_1.13.0.tar.gz
Windows Binary biotmle_1.13.0.zip
macOS 10.13 (High Sierra) biotmle_1.13.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/biotmle
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/biotmle
Package Short Url https://bioconductor.org/packages/biotmle/
Package Downloads Report Download Stats

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