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Shaped singular spectrum analysis for quantifying gene expression, with application to the early Drosophila embryo.

Shlemov A, Golyandina N, Holloway D, Spirov A - Biomed Res Int (2015)

Bottom Line: We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo.We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes.Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Mathematics and Mechanics, St. Petersburg State University, Universitetsky Pr. 28, Peterhof, St. Petersburg 198504, Russia.

ABSTRACT
In recent years, with the development of automated microscopy technologies, the volume and complexity of image data on gene expression have increased tremendously. The only way to analyze quantitatively and comprehensively such biological data is by developing and applying new sophisticated mathematical approaches. Here, we present extensions of 2D singular spectrum analysis (2D-SSA) for application to 2D and 3D datasets of embryo images. These extensions, circular and shaped 2D-SSA, are applied to gene expression in the nuclear layer just under the surface of the Drosophila (fruit fly) embryo. We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo. We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes. Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns.

No MeSH data available.


Kr and eve: reconstruction with stripe components, from the Kr image (a) and from the eve image (b). The frequencies correspond, but are out-of-phase, indicating overcorrection in the unmixing algorithm.
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fig12: Kr and eve: reconstruction with stripe components, from the Kr image (a) and from the eve image (b). The frequencies correspond, but are out-of-phase, indicating overcorrection in the unmixing algorithm.

Mentions: The decomposition in Figure 10 shows components with low frequency vertical stripes corresponding to the Kr signal, as well as high frequency stripes corresponding to eve. These high frequency stripes can be seen in the eve decomposition (Figure 11), in particular components 4-5, 7–9, 11, 13, 15, 19, and 20. Conversely, Kr crosstalk on the eve image is apparent in Figure 11 in components 9, 10, 13, 15, 20, and 25. Figure 12 shows reconstructions using the stripe components from the images. Again, being a characteristic of overcorrection in the unmixing algorithm, these patterns are of comparable frequency, but of opposite phase.


Shaped singular spectrum analysis for quantifying gene expression, with application to the early Drosophila embryo.

Shlemov A, Golyandina N, Holloway D, Spirov A - Biomed Res Int (2015)

Kr and eve: reconstruction with stripe components, from the Kr image (a) and from the eve image (b). The frequencies correspond, but are out-of-phase, indicating overcorrection in the unmixing algorithm.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4402483&req=5

fig12: Kr and eve: reconstruction with stripe components, from the Kr image (a) and from the eve image (b). The frequencies correspond, but are out-of-phase, indicating overcorrection in the unmixing algorithm.
Mentions: The decomposition in Figure 10 shows components with low frequency vertical stripes corresponding to the Kr signal, as well as high frequency stripes corresponding to eve. These high frequency stripes can be seen in the eve decomposition (Figure 11), in particular components 4-5, 7–9, 11, 13, 15, 19, and 20. Conversely, Kr crosstalk on the eve image is apparent in Figure 11 in components 9, 10, 13, 15, 20, and 25. Figure 12 shows reconstructions using the stripe components from the images. Again, being a characteristic of overcorrection in the unmixing algorithm, these patterns are of comparable frequency, but of opposite phase.

Bottom Line: We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo.We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes.Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Mathematics and Mechanics, St. Petersburg State University, Universitetsky Pr. 28, Peterhof, St. Petersburg 198504, Russia.

ABSTRACT
In recent years, with the development of automated microscopy technologies, the volume and complexity of image data on gene expression have increased tremendously. The only way to analyze quantitatively and comprehensively such biological data is by developing and applying new sophisticated mathematical approaches. Here, we present extensions of 2D singular spectrum analysis (2D-SSA) for application to 2D and 3D datasets of embryo images. These extensions, circular and shaped 2D-SSA, are applied to gene expression in the nuclear layer just under the surface of the Drosophila (fruit fly) embryo. We consider the commonly used cylindrical projection of the ellipsoidal Drosophila embryo. We demonstrate how circular and shaped versions of 2D-SSA help to decompose expression data into identifiable components (such as trend and noise), as well as separating signals from different genes. Detection and improvement of under- and overcorrection in multichannel imaging is addressed, as well as the extraction and analysis of 3D features in 3D gene expression patterns.

No MeSH data available.