Details
| Original language | English |
|---|---|
| Pages (from-to) | 14-26 |
| Number of pages | 13 |
| Journal | R Journal |
| Volume | 9 |
| Issue number | 1 |
| Publication status | Published - 10 May 2017 |
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.
ASJC Scopus subject areas
- Mathematics(all)
- Statistics and Probability
- Mathematics(all)
- Numerical Analysis
- Decision Sciences(all)
- Statistics, Probability and Uncertainty
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In: R Journal, Vol. 9, No. 1, 10.05.2017, p. 14-26.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - IsoGeneGUI
T2 - Multiple approaches for dose-response analysis of microarray data using R
AU - Otava, Martin
AU - Sengupta, Rudradev
AU - Shkedy, Ziv
AU - Lin, Dan
AU - Pramana, Setia
AU - Verbeke, Tobias
AU - Haldermans, Philippe
AU - Hothorn, Ludwig A.
AU - Gerhard, Daniel
AU - Kuiper, Rebecca M.
AU - Klinglmueller, Florian
AU - Kasim, Adetayo
PY - 2017/5/10
Y1 - 2017/5/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85021453192&partnerID=8YFLogxK
U2 - 10.32614/rj-2017-002
DO - 10.32614/rj-2017-002
M3 - Article
AN - SCOPUS:85021453192
VL - 9
SP - 14
EP - 26
JO - R Journal
JF - R Journal
SN - 2073-4859
IS - 1
ER -