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Matching of array CGH and gene expression microarray features for the purpose of integrative genomic analyses.

van Wieringen WN, Unger K, Leday GG, Krijgsman O, de Menezes RX, Ylstra B, van de Wiel MA - BMC Bioinformatics (2012)

Bottom Line: Although important, many integrative analyses do not or insufficiently detail the matching of the platforms.Illustration of the matching procedures on a variety of data sets reveals how the procedures differ in the use of the available data, and may even lead to different results for individual genes.Matching of data from multiple genomics platforms is an important preprocessing step for many integrative bioinformatic analysis, for which we present six generic procedures, both old and new.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl

ABSTRACT

Background: An increasing number of genomic studies interrogating more than one molecular level is published. Bioinformatics follows biological practice, and recent years have seen a surge in methodology for the integrative analysis of genomic data. Often such analyses require knowledge of which elements of one platform link to those of another. Although important, many integrative analyses do not or insufficiently detail the matching of the platforms.

Results: We describe, illustrate and discuss six matching procedures. They are implemented in the R-package sigaR (available from Bioconductor). The principles underlying the presented matching procedures are generic, and can be combined to form new matching approaches or be applied to the matching of other platforms. Illustration of the matching procedures on a variety of data sets reveals how the procedures differ in the use of the available data, and may even lead to different results for individual genes.

Conclusions: Matching of data from multiple genomics platforms is an important preprocessing step for many integrative bioinformatic analysis, for which we present six generic procedures, both old and new. They have been implemented in the R-package sigaR, available from Bioconductor.

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Related in: MedlinePlus

Label matching: an ID is sought within a large set of IDs. The dashed arrow indicates that the gene’s ID has been found in the pile of DNA copy number IDs.
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Figure 1: Label matching: an ID is sought within a large set of IDs. The dashed arrow indicates that the gene’s ID has been found in the pile of DNA copy number IDs.

Mentions: The first matching procedure uses the feature labels (e.g., manufacturer IDs) of both arrays. Both sets of labels are mapped to a common descriptor set, e.g., the gene symbol. These maps are exploited to link the features of the two platforms, and features of both platforms are matched if they map to the same common descriptor. See Lo et al. [28] for an application of this procedure. Table 1 describes the procedure algorithmically, while it is depicted visually in Figure 1.


Matching of array CGH and gene expression microarray features for the purpose of integrative genomic analyses.

van Wieringen WN, Unger K, Leday GG, Krijgsman O, de Menezes RX, Ylstra B, van de Wiel MA - BMC Bioinformatics (2012)

Label matching: an ID is sought within a large set of IDs. The dashed arrow indicates that the gene’s ID has been found in the pile of DNA copy number IDs.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475006&req=5

Figure 1: Label matching: an ID is sought within a large set of IDs. The dashed arrow indicates that the gene’s ID has been found in the pile of DNA copy number IDs.
Mentions: The first matching procedure uses the feature labels (e.g., manufacturer IDs) of both arrays. Both sets of labels are mapped to a common descriptor set, e.g., the gene symbol. These maps are exploited to link the features of the two platforms, and features of both platforms are matched if they map to the same common descriptor. See Lo et al. [28] for an application of this procedure. Table 1 describes the procedure algorithmically, while it is depicted visually in Figure 1.

Bottom Line: Although important, many integrative analyses do not or insufficiently detail the matching of the platforms.Illustration of the matching procedures on a variety of data sets reveals how the procedures differ in the use of the available data, and may even lead to different results for individual genes.Matching of data from multiple genomics platforms is an important preprocessing step for many integrative bioinformatic analysis, for which we present six generic procedures, both old and new.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl

ABSTRACT

Background: An increasing number of genomic studies interrogating more than one molecular level is published. Bioinformatics follows biological practice, and recent years have seen a surge in methodology for the integrative analysis of genomic data. Often such analyses require knowledge of which elements of one platform link to those of another. Although important, many integrative analyses do not or insufficiently detail the matching of the platforms.

Results: We describe, illustrate and discuss six matching procedures. They are implemented in the R-package sigaR (available from Bioconductor). The principles underlying the presented matching procedures are generic, and can be combined to form new matching approaches or be applied to the matching of other platforms. Illustration of the matching procedures on a variety of data sets reveals how the procedures differ in the use of the available data, and may even lead to different results for individual genes.

Conclusions: Matching of data from multiple genomics platforms is an important preprocessing step for many integrative bioinformatic analysis, for which we present six generic procedures, both old and new. They have been implemented in the R-package sigaR, available from Bioconductor.

Show MeSH
Related in: MedlinePlus