DOI: 10.18129/B9.bioc.biotmle    

This package is for version 3.8 of Bioconductor; for the stable, up-to-date release version, see biotmle.

Targeted Learning with Moderated Statistics for Biomarker Discovery

Bioconductor version: 3.8

This package facilitates the discovery of biomarkers from biological sequencing data (e.g., microarrays, RNA-seq) based on the associations of potential biomarkers with exposure and outcome variables by implementing an estimation procedure that combines a generalization of moderated statistics with targeted minimum loss-based estimates (TMLE) of parameters defined via causal inference (e.g., Average Treatment Effect) whose estimators admit asymptotically linear representations.

Author: Nima Hejazi [aut, cre, cph], Alan Hubbard [aut, ths], Weixin Cai [ctb]

Maintainer: Nima Hejazi <nhejazi at>

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


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HTML R Script Identifying Biomarkers from an Exposure Variable
HTML R Script Processing and Analyzing RNA-Seq Data
PDF   Reference Manual
Text   NEWS


biocViews DifferentialExpression, GeneExpression, Microarray, RNASeq, Sequencing, Software
Version 1.6.0
In Bioconductor since BioC 3.5 (R-3.4) (2 years)
License file LICENSE
Depends R (>= 3.4)
Imports dplyr, ggplot2, ggsci, superheat, doFuture, future, stats, methods, limma, S4Vectors, BiocGenerics, BiocParallel, SummarizedExperiment, tmle
Suggests testthat, knitr, rmarkdown, BiocStyle, SuperLearner, Matrix, DBI, biotmleData(>= 1.1.1)
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