IsoGeneGUI: Multiple Approaches for Dose-Response Analysis of Microarray Data Using R
Martin Otava, Rudradev Sengupta, Ziv Shkedy, Dan Lin, Setia Pramana, Tobias Verbeke, Philippe Haldermans, Ludwig A. Hothorn, Daniel Gerhard, Rebecca M. Kuiper, Florian Klinglmueller and Adetayo Kasim
, The R Journal (2017) 9:1, pages 14-26.
Abstract The analysis of transcriptomic experiments with ordered covariates, such as dose-response data, has become a central topic in bioinformatics, in particular in omics studies. Consequently, multiple R packages on CRAN and Bioconductor are designed to analyse microarray data from various perspectives under the assumption of order restriction. We introduce the new R package IsoGene Graphical User Interface (IsoGeneGUI), an extension of the original IsoGene package that includes methods from most of available R packages designed for the analysis of order restricted microarray data, namely orQA, ORIClust, goric and ORCME. The methods included in the new IsoGeneGUI range from inference and estimation to model selection and clustering tools. The IsoGeneGUI is not only the most complete tool for the analysis of order restricted microarray experiments available in R but also it can be used to analyse other types of dose-response data. The package provides all the methods in a user friendly fashion, so analyses can be implemented by users with limited knowledge of R programming.
Received: 2015-07-22; online 2017-05-10@article{RJ-2017-002, author = {Martin Otava and Rudradev Sengupta and Ziv Shkedy and Dan Lin and Setia Pramana and Tobias Verbeke and Philippe Haldermans and Ludwig A. Hothorn and Daniel Gerhard and Rebecca M. Kuiper and Florian Klinglmueller and Adetayo Kasim}, title = {{IsoGeneGUI: Multiple Approaches for Dose-Response Analysis of Microarray Data Using R}}, year = {2017}, journal = {{The R Journal}}, doi = {10.32614/RJ-2017-002}, url = {https://doi.org/10.32614/RJ-2017-002}, pages = {14--26}, volume = {9}, number = {1} }