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# R/`biotmle` [![Travis-CI Build Status](]( [![AppVeyor Build Status](]( [![Coverage Status](]( [![Project Status: WIP - Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](]( [![MIT license](]( > Targeted Learning with moderated statistics for biomarker discovery --- ## Description `biotmle` is an R package that facilitates biomarker discovery by generalizing the moderated t-statistic of Smyth for use with asymptotically linear target parameters. The set of methods implemented in this R package rely on the use of Targeted Minimum Loss-Based Estimation (TMLE) to transform biological sequencing data (e.g., microarray, RNA-seq) based on the influence curve representation of a particular causal target parameter (e.g., Average Treatment Effect). The transformed data are then used to test for differences between the statistical estimate of the target parameter and a hypothesized value of said parameter using the approach of moderated statistics implemented in the R package [`limma`]( --- ## Installation - For standard use, install from [Bioconductor]( ``` source("") biocLite("biotmle") ``` - Install the most recent _stable release_ from GitHub: ``` devtools::install_github("nhejazi/biotmle") ``` - To contribute, install the _development version_: ``` devtools::install_github("nhejazi/biotmle", ref = "develop") ``` --- ## Issues If you encounter any bugs or have any specific feature requests, please [file an issue]( --- ## Citation After using the `biotmle` R package, please cite it: @article{hejazi2017biotmle, doi = {}, url = {}, year = {2017}, month = {}, publisher = {The Open Journal}, volume = {}, number = {}, author = {Hejazi, Nima S and Cai, Weixin and Hubbard, Alan E}, title = {biotmle: Targeted Learning for Biomarker Discovery}, journal = {The Journal of Open Source Software} } --- ## Related * [R/`biotmleData`]( - R package with example experimental data for use with this analysis package. --- ## References * [Nima S. Hejazi, Sara Kherad-Pajouh, Mark J. van der Laan, and Alan E. Hubbard. "Generalized application of the moderated t-statistic to asymptotically linear target parameters." __in preparation__, 2017.]() * [Gordon K. Smyth. "Linear models and empirical Bayes methods for assessing differential expression in microarray experiments." _Statistical Applications in Genetics and Molecular Biology_, 3(1), 2004.]( --- ## License © 2016-2017 [Nima S. Hejazi]( & [Alan E. Hubbard]( The contents of this repository are distributed under the MIT license. See file `LICENSE` for details.