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DepthTools: an R package for a robust analysis of gene expression data
Aurora Torrente1, Sara López-Pintado, Juan Romo
1Functional Genomics Team, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK. aurora@ebi.ac.uk
BMC Bioinformatics
|July 27, 2013
Summary
This study introduces depthTools, an R package offering robust statistical analysis for high-dimensional gene expression data. It aids in understanding tumor variations and developing personalized treatments.
Area of Science:
- Bioinformatics
- Statistical Genetics
Background:
- High-density DNA microarrays and oligonucleotide chips generate complex, high-dimensional data crucial for gene expression analysis and disease diagnosis.
- Existing statistical methods may not be sufficiently robust for analyzing this complex genomic data.
Purpose of the Study:
- To develop and present a novel R package, depthTools, for robust statistical analysis of gene expression data.
- To provide tools for visualization and inference applicable to high-dimensional genomic datasets.
Main Methods:
- Utilizes an efficient implementation of Modified Band Depth for robust statistical analysis.
- The depthTools package is implemented in R, a widely used statistical programming language.
- Includes a user-friendly interface via an R-commander plugin.
Main Results:
- depthTools provides robust statistical analysis for gene expression data.
- The package offers effective visualization and inference tools for high-dimensional data.
- Successfully applied to analyze complex genomic datasets.
Conclusions:
- The depthTools package demonstrates utility in analyzing genome-level variation between tumors.
- Facilitates a better understanding of tumor heterogeneity.
- Supports the development of personalized treatment strategies.
