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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

Scale curves of normal and tumor prostate samples. Scale curves for the normal and tumor samples included in the prostate data. The tumor samples (dashed line) have in general a larger dispersion than the normal ones (solid line). The red dot represents the spread of the 25% most central normal samples.
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Figure 4: Scale curves of normal and tumor prostate samples. Scale curves for the normal and tumor samples included in the prostate data. The tumor samples (dashed line) have in general a larger dispersion than the normal ones (solid line). The red dot represents the spread of the 25% most central normal samples.

Mentions: As it can be seen in Figure4, though the dispersion of both types of samples are similar, the tumor ones are more spread in general. In particular, the red dot in Figure4 corresponds to the variability of the 25% deepest normal curves, and represents the area of the 0.25-band in Figure1(b).


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

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

Scale curves of normal and tumor prostate samples. Scale curves for the normal and tumor samples included in the prostate data. The tumor samples (dashed line) have in general a larger dispersion than the normal ones (solid line). The red dot represents the spread of the 25% most central normal samples.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 4: Scale curves of normal and tumor prostate samples. Scale curves for the normal and tumor samples included in the prostate data. The tumor samples (dashed line) have in general a larger dispersion than the normal ones (solid line). The red dot represents the spread of the 25% most central normal samples.
Mentions: As it can be seen in Figure4, though the dispersion of both types of samples are similar, the tumor ones are more spread in general. In particular, the red dot in Figure4 corresponds to the variability of the 25% deepest normal curves, and represents the area of the 0.25-band in Figure1(b).

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