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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 plots. (a) Representation in parallel coordinates of 25 normal prostate samples, with the deepest one depicted in red. (b) MBD-based bands, for different proportions of central points (grayscale regions), corresponding to 25 normal prostate samples with respect to 25 cancer prostate samples (blue lines). The normal sample which lies the deepest in the reference collection of tumor ones is drawn in red.
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Figure 1: MBD plots. (a) Representation in parallel coordinates of 25 normal prostate samples, with the deepest one depicted in red. (b) MBD-based bands, for different proportions of central points (grayscale regions), corresponding to 25 normal prostate samples with respect to 25 cancer prostate samples (blue lines). The normal sample which lies the deepest in the reference collection of tumor ones is drawn in red.

Mentions: To illustrate the use of the function MBD, we apply it to the data set prostate, included in the package. In particular, Figure1 is obtained with the following code:


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

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

MBD plots. (a) Representation in parallel coordinates of 25 normal prostate samples, with the deepest one depicted in red. (b) MBD-based bands, for different proportions of central points (grayscale regions), corresponding to 25 normal prostate samples with respect to 25 cancer prostate samples (blue lines). The normal sample which lies the deepest in the reference collection of tumor ones is drawn in red.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: MBD plots. (a) Representation in parallel coordinates of 25 normal prostate samples, with the deepest one depicted in red. (b) MBD-based bands, for different proportions of central points (grayscale regions), corresponding to 25 normal prostate samples with respect to 25 cancer prostate samples (blue lines). The normal sample which lies the deepest in the reference collection of tumor ones is drawn in red.
Mentions: To illustrate the use of the function MBD, we apply it to the data set prostate, included in the package. In particular, Figure1 is obtained with the following code:

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