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Array data extractor (ADE): a LabVIEW program to extract and merge gene array data.

Kurtenbach S, Kurtenbach S, Zoidl G - BMC Res Notes (2013)

Bottom Line: Results confirmed known regulation of a beta 1 adrenergic receptor and further indicate novel research targets.Although existing software allows for complex data analyses, the LabVIEW based program presented here, "Array Data Extractor (ADE)", provides users with a tool to retrieve meaningful information from multiple normalized gene expression datasets in a fast and easy way.Further, the graphical programming language used in LabVIEW allows applying changes to the program without the need of advanced programming knowledge.

View Article: PubMed Central - HTML - PubMed

Affiliation: Faculty of Health, Department of Psychology, Molecular and Cellular Neuroscience, York University, LSB 323A, 4700 Keele Street, Toronto, ON M3J 1P3, Canada. Stefan.Kurtenbach@me.com.

ABSTRACT

Background: Large data sets from gene expression array studies are publicly available offering information highly valuable for research across many disciplines ranging from fundamental to clinical research. Highly advanced bioinformatics tools have been made available to researchers, but a demand for user-friendly software allowing researchers to quickly extract expression information for multiple genes from multiple studies persists.

Findings: Here, we present a user-friendly LabVIEW program to automatically extract gene expression data for a list of genes from multiple normalized microarray datasets. Functionality was tested for 288 class A G protein-coupled receptors (GPCRs) and expression data from 12 studies comparing normal and diseased human hearts. Results confirmed known regulation of a beta 1 adrenergic receptor and further indicate novel research targets.

Conclusions: Although existing software allows for complex data analyses, the LabVIEW based program presented here, "Array Data Extractor (ADE)", provides users with a tool to retrieve meaningful information from multiple normalized gene expression datasets in a fast and easy way. Further, the graphical programming language used in LabVIEW allows applying changes to the program without the need of advanced programming knowledge.

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Related in: MedlinePlus

Program interface. While running, the program will indicate which genes were found in the dataset, which ones were not present in the array annotation (Annotation.txt file), and which genes are present in the chip annotation but not in the dataset. Progress bars indicate progress for data extraction, refinement, merging, and statistics. Statistics will only be performed when button is activated. In the settings tab on the left, the user can choose between median and mean values to be used for spot selection and ratio calculations. Further, Stouffer’s Z-transform method or Fisher’s method can be chosen to combine p-values from the studies. The user can also chose between automatic Log2 detection, or manual definition. In the latter case “NOLOG” has to be assigned to the folder names of the studies not Log2 transformed.
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Figure 2: Program interface. While running, the program will indicate which genes were found in the dataset, which ones were not present in the array annotation (Annotation.txt file), and which genes are present in the chip annotation but not in the dataset. Progress bars indicate progress for data extraction, refinement, merging, and statistics. Statistics will only be performed when button is activated. In the settings tab on the left, the user can choose between median and mean values to be used for spot selection and ratio calculations. Further, Stouffer’s Z-transform method or Fisher’s method can be chosen to combine p-values from the studies. The user can also chose between automatic Log2 detection, or manual definition. In the latter case “NOLOG” has to be assigned to the folder names of the studies not Log2 transformed.

Mentions: The program interface is depicted in Figure 2. Once started, ADE will perform a series of tasks, which are summarized in Figure 3. First, the software will extract all data for the genes defined (or e.g. Entrez IDs) in “Genes of interest.txt” from the “Data.txt” files. Extracted data will be saved in a new folder called “Extracted Data” for each study individually as “output.txt” files. Existing “output.txt” files will not be overwritten, as in some cases complete ADE runs are not needed, for instance when only one new study is added.


Array data extractor (ADE): a LabVIEW program to extract and merge gene array data.

Kurtenbach S, Kurtenbach S, Zoidl G - BMC Res Notes (2013)

Program interface. While running, the program will indicate which genes were found in the dataset, which ones were not present in the array annotation (Annotation.txt file), and which genes are present in the chip annotation but not in the dataset. Progress bars indicate progress for data extraction, refinement, merging, and statistics. Statistics will only be performed when button is activated. In the settings tab on the left, the user can choose between median and mean values to be used for spot selection and ratio calculations. Further, Stouffer’s Z-transform method or Fisher’s method can be chosen to combine p-values from the studies. The user can also chose between automatic Log2 detection, or manual definition. In the latter case “NOLOG” has to be assigned to the folder names of the studies not Log2 transformed.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4222097&req=5

Figure 2: Program interface. While running, the program will indicate which genes were found in the dataset, which ones were not present in the array annotation (Annotation.txt file), and which genes are present in the chip annotation but not in the dataset. Progress bars indicate progress for data extraction, refinement, merging, and statistics. Statistics will only be performed when button is activated. In the settings tab on the left, the user can choose between median and mean values to be used for spot selection and ratio calculations. Further, Stouffer’s Z-transform method or Fisher’s method can be chosen to combine p-values from the studies. The user can also chose between automatic Log2 detection, or manual definition. In the latter case “NOLOG” has to be assigned to the folder names of the studies not Log2 transformed.
Mentions: The program interface is depicted in Figure 2. Once started, ADE will perform a series of tasks, which are summarized in Figure 3. First, the software will extract all data for the genes defined (or e.g. Entrez IDs) in “Genes of interest.txt” from the “Data.txt” files. Extracted data will be saved in a new folder called “Extracted Data” for each study individually as “output.txt” files. Existing “output.txt” files will not be overwritten, as in some cases complete ADE runs are not needed, for instance when only one new study is added.

Bottom Line: Results confirmed known regulation of a beta 1 adrenergic receptor and further indicate novel research targets.Although existing software allows for complex data analyses, the LabVIEW based program presented here, "Array Data Extractor (ADE)", provides users with a tool to retrieve meaningful information from multiple normalized gene expression datasets in a fast and easy way.Further, the graphical programming language used in LabVIEW allows applying changes to the program without the need of advanced programming knowledge.

View Article: PubMed Central - HTML - PubMed

Affiliation: Faculty of Health, Department of Psychology, Molecular and Cellular Neuroscience, York University, LSB 323A, 4700 Keele Street, Toronto, ON M3J 1P3, Canada. Stefan.Kurtenbach@me.com.

ABSTRACT

Background: Large data sets from gene expression array studies are publicly available offering information highly valuable for research across many disciplines ranging from fundamental to clinical research. Highly advanced bioinformatics tools have been made available to researchers, but a demand for user-friendly software allowing researchers to quickly extract expression information for multiple genes from multiple studies persists.

Findings: Here, we present a user-friendly LabVIEW program to automatically extract gene expression data for a list of genes from multiple normalized microarray datasets. Functionality was tested for 288 class A G protein-coupled receptors (GPCRs) and expression data from 12 studies comparing normal and diseased human hearts. Results confirmed known regulation of a beta 1 adrenergic receptor and further indicate novel research targets.

Conclusions: Although existing software allows for complex data analyses, the LabVIEW based program presented here, "Array Data Extractor (ADE)", provides users with a tool to retrieve meaningful information from multiple normalized gene expression datasets in a fast and easy way. Further, the graphical programming language used in LabVIEW allows applying changes to the program without the need of advanced programming knowledge.

Show MeSH
Related in: MedlinePlus