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DepthTools: an R package for a robust analysis of gene expression data.

Torrente A, López-Pintado S, Romo J - BMC Bioinformatics (2013)

Bottom Line: Therefore, there is a need for developing new, robust statistical techniques to analyze these data. depthTools is an R package for a robust statistical analysis of gene expression data, based on an efficient implementation of a feasible notion of depth, the Modified Band Depth.This software includes several visualization and inference tools successfully applied to high dimensional gene expression data.A user-friendly interface is also provided via an R-commander plugin.

View Article: PubMed Central - HTML - PubMed

Affiliation: Functional Genomics Team, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK. aurora@ebi.ac.uk

ABSTRACT

Background: The use of DNA microarrays and oligonucleotide chips of high density in modern biomedical research provides complex, high dimensional data which have been proven to convey crucial information about gene expression levels and to play an important role in disease diagnosis. Therefore, there is a need for developing new, robust statistical techniques to analyze these data.

Results: depthTools is an R package for a robust statistical analysis of gene expression data, based on an efficient implementation of a feasible notion of depth, the Modified Band Depth. This software includes several visualization and inference tools successfully applied to high dimensional gene expression data. A user-friendly interface is also provided via an R-commander plugin.

Conclusion: We illustrate the utility of the depthTools package, that could be used, for instance, to achieve a better understanding of genome-level variation between tumors and to facilitate the development of personalized treatments.

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Related in: MedlinePlus

MBD windows. (a) Main window for the MBD computation in the R-commander. (b) Graphical window for adjusting the appearance of the MBD plot. (c) Output window for selecting which computations are stored as R objects.
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Figure 6: MBD windows. (a) Main window for the MBD computation in the R-commander. (b) Graphical window for adjusting the appearance of the MBD plot. (c) Output window for selecting which computations are stored as R objects.

Mentions: As an example, we show the interface for the computation of MBD (see Figure6(a)). Once the R-commander active dataset has been chosen, if we select ‘Compute Modified Band Depth...’ in the menu bar (Figure5), the main window pops up and allows deciding whether the depth is computed with respect to the given sample or with respect to a different one. The user can also obtain the plot produced by the function MBD, and adjust its appearance with the Graphical options button (see Figure6(b)). The outputs of the MBD computations are the depth and the order position from center outwards of each point, and can be selected to be stored as R objects (vectors) with the Outputs button (see Figure6(c)).


DepthTools: an R package for a robust analysis of gene expression data.

Torrente A, López-Pintado S, Romo J - BMC Bioinformatics (2013)

MBD windows. (a) Main window for the MBD computation in the R-commander. (b) Graphical window for adjusting the appearance of the MBD plot. (c) Output window for selecting which computations are stored as R objects.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3750619&req=5

Figure 6: MBD windows. (a) Main window for the MBD computation in the R-commander. (b) Graphical window for adjusting the appearance of the MBD plot. (c) Output window for selecting which computations are stored as R objects.
Mentions: As an example, we show the interface for the computation of MBD (see Figure6(a)). Once the R-commander active dataset has been chosen, if we select ‘Compute Modified Band Depth...’ in the menu bar (Figure5), the main window pops up and allows deciding whether the depth is computed with respect to the given sample or with respect to a different one. The user can also obtain the plot produced by the function MBD, and adjust its appearance with the Graphical options button (see Figure6(b)). The outputs of the MBD computations are the depth and the order position from center outwards of each point, and can be selected to be stored as R objects (vectors) with the Outputs button (see Figure6(c)).

Bottom Line: Therefore, there is a need for developing new, robust statistical techniques to analyze these data. depthTools is an R package for a robust statistical analysis of gene expression data, based on an efficient implementation of a feasible notion of depth, the Modified Band Depth.This software includes several visualization and inference tools successfully applied to high dimensional gene expression data.A user-friendly interface is also provided via an R-commander plugin.

View Article: PubMed Central - HTML - PubMed

Affiliation: Functional Genomics Team, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK. aurora@ebi.ac.uk

ABSTRACT

Background: The use of DNA microarrays and oligonucleotide chips of high density in modern biomedical research provides complex, high dimensional data which have been proven to convey crucial information about gene expression levels and to play an important role in disease diagnosis. Therefore, there is a need for developing new, robust statistical techniques to analyze these data.

Results: depthTools is an R package for a robust statistical analysis of gene expression data, based on an efficient implementation of a feasible notion of depth, the Modified Band Depth. This software includes several visualization and inference tools successfully applied to high dimensional gene expression data. A user-friendly interface is also provided via an R-commander plugin.

Conclusion: We illustrate the utility of the depthTools package, that could be used, for instance, to achieve a better understanding of genome-level variation between tumors and to facilitate the development of personalized treatments.

Show MeSH
Related in: MedlinePlus